From 6f847d4b062d3d5115f209ee965fc08a146cc872 Mon Sep 17 00:00:00 2001 From: Maziyar Panahi Date: Thu, 26 Oct 2023 10:52:17 +0200 Subject: [PATCH] Models hub (#14042) --------- Co-authored-by: ahmedlone127 * 2023-09-13-bert_base_uncased_issues_128_juandeun_en (#13981) * Add model 2023-09-13-b_fb_sms_lm_en * Add model 2023-09-13-kannada_bert_kn * Add model 2023-09-13-bert_base_uncased_finetuned_bert_auto7_en * Add model 2023-09-13-betonews_tweetcontext_en * Add model 2023-09-13-bert_twitter_hashtag_en * Add model 2023-09-13-bert_base_cased_finetuned_bert_auto7_en * Add model 2023-09-13-telugu_bert_te * Add model 2023-09-13-arab_bert_en * Add model 2023-09-13-bert_base_uncased_finetuned_bert_mlm_en * Add model 2023-09-13-ct_pubmedbert_re_en * Add model 2023-09-13-mybert_mini_500k_en * Add model 2023-09-13-malayalam_bert_ml * Add model 2023-09-13-mybert_mini_1m_en * Add model 2023-09-13-phrase_bert_finetuned_imdb_en * Add model 2023-09-13-bert_large_uncased_whole_word_masking_finetuned_bert_mlm_en * Add model 2023-09-13-berdou_200k_en * Add model 2023-09-13-tamil_bert_ta * Add model 2023-09-13-legal_hebert_en * Add model 2023-09-13-bert_base_uncased_finetuned_imdb_sarmila_en * Add model 2023-09-13-berdou_500k_en * Add model 2023-09-13-bert_large_uncased_finetuned_bert_mlm5_en * Add model 2023-09-13-alephbertgimmel_small_128_he * Add model 2023-09-13-gujarati_bert_gu * Add model 2023-09-13-alberti_bert_base_multilingual_cased_flax_community_xx * Add model 2023-09-13-bert_base_japanese_ssuw_ja * Add model 2023-09-13-bert_base_cased_finetuned_bert_mlm5_en * Add model 2023-09-13-roberta_base_culinary_en * Add model 2023-09-13-bert_base_uncased_swahili_sw * Add model 2023-09-13-assamese_bert_as * Add model 2023-09-13-cocodr_base_msmarco_warmup_en * Add model 2023-09-13-shangpin_pre_training_en * Add model 2023-09-13-bert_large_cased_whole_word_masking_finetuned_bert_mlm6_en * Add model 2023-09-13-reddit_bert_text2_en * Add model 2023-09-13-legal_indobert_pytorch_v4_en * Add model 2023-09-13-bert_base_uncased_finetuned_bert_mlm9_en * Add model 2023-09-13-reddit_bert_text3_en * Add model 2023-09-13-odia_bert_or * Add model 2023-09-13-luxembert_en * Add model 2023-09-13-mbert_deen_en * Add model 2023-09-13-reddit_bert_text4_en * Add model 2023-09-13-bengali_bert_bn * Add model 2023-09-13-reddit_bert_text_10_en * Add model 2023-09-13-kcbert_large_finetuned_en * Add model 2023-09-13-reddit_bert_text_20_en * Add model 2023-09-13-punjabi_bert_pa * Add model 2023-09-13-bert_base_uncased_issues_128_cj_mills_en * Add model 2023-09-13-bert_base_uncased_finetuned_himani_gen_mlm_en * Add model 2023-09-13-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_0_en * Add model 2023-09-13-reddit_bert_text_5_en * Add model 2023-09-13-dapbert_en * Add model 2023-09-13-bert_base_uncased_finetuned_himani_gen_mlm_1_en * Add model 2023-09-13-youtube_bert_en * Add model 2023-09-13-pretrained_kyw_e1_en * Add model 2023-09-13-dapscibert_en * Add model 2023-09-13-bert_base_uncased_finetuned_himani_gen_mlm_12_en * Add model 2023-09-13-youtube_bert_10_en * Add model 2023-09-13-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_1_en * Add model 2023-09-13-bert_pretraining_gaudi_2_batch_size_32_en * Add model 2023-09-13-model1_en * Add model 2023-09-13-klue_base_finetuned_en * Add model 2023-09-13-me_bert_mr * Add model 2023-09-13-bert_cluster_en * Add model 2023-09-13-medical_bio_bert2_en * Add model 2023-09-13-bert_base_uncased_finetuned_himani_gen_mlm_13_en * Add model 2023-09-13-me_bert_mixed_mr * Add model 2023-09-13-bert_large_cased_finetuned_hkdse_english_paper4_en * Add model 2023-09-13-dabert_multi_en * Add model 2023-09-13-bert_base_uncased_finetuned_himani_gen_mlm_14_en * Add model 2023-09-13-bert_base_spanish_amvv_uncased_en * Add model 2023-09-13-manubert_en * Add model 2023-09-13-greeksocialbert_base_greek_uncased_v1_el * Add model 2023-09-13-bert_base_uncased_finetuned_himani_gen_mlm_15_en * Add model 2023-09-13-bert_base_pashto_v1_ps * Add model 2023-09-13-parlbert_german_v1_de * Add model 2023-09-13-bert_pretraining_gaudi_2_batch_size_64_en * Add model 2023-09-13-bert_base_cased_portuguese_c_corpus_en * Add model 2023-09-13-testc8_1_en * Add model 2023-09-13-klue_bert_epoch3_en * Add model 2023-09-13-bert_base_stackoverflow_comments_1m_en * Add model 2023-09-13-testc8_2_en * Add model 2023-09-13-bert_base_stackoverflow_comments_2m_en * Add model 2023-09-13-kcbert_base_finetuned_en * Add model 2023-09-13-bert_base_arabic_miner_en * Add model 2023-09-14-bert_base_greek_uncased_v5_finetuned_polylex_malagasy_en * Add model 2023-09-14-dummy_model_linbo_en * Add model 2023-09-14-bert_base_code_comments_en * Add model 2023-09-14-bert_base_greek_uncased_v6_finetuned_polylex_malagasy_en * Add model 2023-09-14-bert_base_uncased_narsil_en * Add model 2023-09-14-bertugues_base_portuguese_cased_pt * Add model 2023-09-14-bert_large_stackoverflow_comments_1m_en * Add model 2023-09-14-retromae_msmarco_distill_en * Add model 2023-09-14-archaeobert_en * Add model 2023-09-14-klue_bert_mlm_en * Add model 2023-09-14-bert_base_uncased_issues_128_mabrouk_en * Add model 2023-09-14-legalbert_large_1.7m_1_en * Add model 2023-09-14-telugu_bert_scratch_te * Add model 2023-09-14-muril_base_cased_en * Add model 2023-09-14-malayalam_bert_scratch_ml * Add model 2023-09-14-weights_bert_mlm_epoch50_en * Add model 2023-09-14-bert_base_cased_conversational_finetuned_wallisian_en * Add model 2023-09-14-mbert_squad_en * Add model 2023-09-14-gujarati_bert_scratch_gu * Add model 2023-09-14-9.4aistudy_en * Add model 2023-09-14-bert_base_uncased_issues_128_veeps_en * Add model 2023-09-14-bert_base_german_europeana_td_cased_en * Add model 2023-09-14-kannada_bert_scratch_kn * Add model 2023-09-14-bert_base_uncased_issues_128_bh8648_en * Add model 2023-09-14-awesome_align_with_corsican_xx * Add model 2023-09-14-bert_base_kor_v1_en * Add model 2023-09-14-bert_base_uncased_finetuned_wallisian_en * Add model 2023-09-14-test_dushen_en * Add model 2023-09-14-bert_base_uncased_finetuned_wallisian_lower_en * Add model 2023-09-14-legalbert_large_1.7m_2_en * Add model 2023-09-14-domain_adapted_arbert_goudma_bert_en * Add model 2023-09-14-medbert_512_norwegian_duplicates_de * Add model 2023-09-14-closure_system_door_inne_bert_base_uncased_en * Add model 2023-09-14-gepabert_de * Add model 2023-09-14-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_5_en * Add model 2023-09-14-bert_system_en * Add model 2023-09-14-mergedistill_base_cased_anneal_en * Add model 2023-09-14-aligner_english_vietnamese_en * Add model 2023-09-14-medbit_r3_plus_it * Add model 2023-09-14-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_6_en * Add model 2023-09-14-mymodel_en * Add model 2023-09-14-door_inner_with_sa_bert_base_uncased_en * Add model 2023-09-14-public_models_en * Add model 2023-09-14-frpile_mlm_en * Add model 2023-09-14-radbert_en * Add model 2023-09-14-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_7_en * Add model 2023-09-14-bert_application_en * Add model 2023-09-14-legal_hebert_ft_en * Add model 2023-09-14-mlm_20230416_003_1_en * Add model 2023-09-14-vatestnew_en * Add model 2023-09-14-dzarabert_ar * Add model 2023-09-14-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_10_en * Add model 2023-09-14-alephbertgimmel_base_512_he * Add model 2023-09-14-mergedistill_base_cased_anneal_v4_en * Add model 2023-09-14-mvr_squad_bert_base_multilingual_cased_xx * Add model 2023-09-14-mlm_20230416_003_2_en * Add model 2023-09-14-medbit_it * Add model 2023-09-14-bert_base_uncased_mlm_scirepeval_fos_chemistry_en * Add model 2023-09-14-medruberttiny2_ru * Add model 2023-09-14-bert_base_uncased_issues_128_abhilashawasthi_en * Add model 2023-09-14-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_11_en * Add model 2023-09-14-sagorbert_nwp_finetuning_test2_en * Add model 2023-09-14-bert_base_uncased_reviews_128_en * Add model 2023-09-14-biobit_it * Add model 2023-09-14-bert_base_uncased_issues_128_reaverlee_en * Add model 2023-09-14-bert_nlp_project_imdb_en * Add model 2023-09-14-biomedvlp_cxr_bert_general_en * Add model 2023-09-14-bert_base_uncased_finetuned_char_hangman_en * Add model 2023-09-14-clinicaltrialbiobert_en * Add model 2023-09-14-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_12_en * Add model 2023-09-14-mlperf_inference_bert_pytorch_fp32_squad_v1.1_en * Add model 2023-09-14-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_13_en * Add model 2023-09-14-bert_base_bookcorpus_en * Add model 2023-09-14-autotrain_acc_keys_2347073860_en * Add model 2023-09-14-ucb_bert_finetunned_en * Add model 2023-09-14-bert_nlp_project_google_en * Add model 2023-09-14-bert_base_wikitext_en * Add model 2023-09-14-bert_large_cased_sigir_support_refute_norwegian_label_40_2nd_test_lr10_8_20_en * Add model 2023-09-14-splade_cocondenser_selfdistil_naver_en * Add model 2023-09-14-jobs_pretraining_model_en * Add model 2023-09-14-logion_50k_wordpiece_en * Add model 2023-09-14-splade_cocondenser_ensembledistil_en * Add model 2023-09-14-bert_based_ner_models_en * Add model 2023-09-14-model_imdb_finetuned_en * Add model 2023-09-14-bnlp_tokenizer_paraphrase_mlm_bert_900001_en * Add model 2023-09-14-gbert_large_finetuned_cust_en * Add model 2023-09-14-project3_model_en * Add model 2023-09-14-bert_base_cased_finetuned_chemistry_en * Add model 2023-09-14-sagorbert_nwp_finetuning_test4_en * Add model 2023-09-14-bert_base_uncased_mlp_scirepeval_chemistry_large_en * Add model 2023-09-14-skc_mlm_german_torch_de * Add model 2023-09-14-kw_pubmed_1000_0.0003_en * Add model 2023-09-14-test_bert_base_uncased_en * Add model 2023-09-14-test_bert_base_spanish_wwm_cased_finetuned_ultrasounds_en * Add model 2023-09-14-akkbert_en * Add model 2023-09-14-kw_pubmed_1000_0.00006_en * Add model 2023-09-14-tiny_mlm_imdb_en * Add model 2023-09-14-tiny_mlm_tweet_en * Add model 2023-09-14-kw_pubmed_1000_0.000006_en * Add model 2023-09-14-oyo_bert_base_yo * Add model 2023-09-14-mini_mlm_tweet_en * Add model 2023-09-14-small_mlm_tweet_en * Add model 2023-09-14-gbert_large_finetuned_cust18_en * Add model 2023-09-14-bert_ucb_v1_en * Add model 2023-09-14-mini_mlm_imdb_en * Add model 2023-09-14-louribert_en * Add model 2023-09-14-medium_mlm_tweet_en * Add model 2023-09-14-applicationbert_en * Add model 2023-09-14-base_mlm_tweet_en * Add model 2023-09-14-bertimbau_pt * Add model 2023-09-14-small_mlm_imdb_en * Add model 2023-09-14-vbert_2021_base_en * Add model 2023-09-14-louribert_more_tokens_saeid7776_en * Add model 2023-09-14-model_saeid7776_en * Add model 2023-09-14-model_v02_en * Add model 2023-09-14-bert_base_uncased_duplicate_en * Add model 2023-09-14-bert_base_minipile_128_en * Add model 2023-09-14-gbert_base_finetuned_twitter_janst_en * Add model 2023-09-14-bert_large_nordic_pile_1m_steps_en * Add model 2023-09-14-bert_large_nordic_pile_1m_steps_sv * Add model 2023-09-14-bibert_v0.1_en * Add model 2023-09-14-bert_base_bangla_finetuned_summarization_dataset_en * Add model 2023-09-14-incorporation_of_company_related_factual_knowledge_into_pre_trained_language_models_en * Add model 2023-09-14-bert_multilang_finetune_bangla_summarization_dataset_en * Add model 2023-09-14-bert_base_uncased_finetuned_wikitext_en * Add model 2023-09-14-antismetisim1_finetuned_mlm_en * Add model 2023-09-14-parlbert_german_law_de * Add model 2023-09-14-dictabert_seg_he * Add model 2023-09-14-dictabert_he * Add model 2023-09-14-dictabert_morph_he * Add model 2023-09-14-scholarbert_100_64bit_en * Add model 2023-09-14-coronasentana_en * Add model 2023-09-14-gbert_large_autopart_en * Add model 2023-09-14-itd_bert_en * Add model 2023-09-14-itd_longformer_en * Add model 2023-09-14-lumbarradiologyreports_en * Add model 2023-09-14-bert_base_german_cased_mlm_basque_chemistry_regulation_en * Add model 2023-09-14-bert_base_spanish_wwm_cased_finetuned_peppa_pig_en * Add model 2023-09-14-bert_base_spanish_wwm_cased_finetuned_wine_reviews_spanish_en * Add model 2023-09-14-antismetisimlargedata_finetuned_mlm_en * Add model 2023-09-14-word_ethical_ko * Add model 2023-09-14-bert_base_cased_finetuned_wallisian_whisper_1ep_en * Add model 2023-09-14-bert_base_cased_finetuned_wallisian_whisper_2ep_en * Add model 2023-09-14-bert_base_cased_finetuned_wallisian_whisper_3ep_en * Add model 2023-09-14-bert_base_cased_finetuned_wallisian_whisper_4ep_en * Add model 2023-09-14-bert_base_cased_finetuned_wallisian_whisper_5ep_en * Add model 2023-09-14-bert_base_cased_finetuned_wallisian_whisper_6ep_en * Add model 2023-09-14-bert_base_cased_finetuned_wallisian_whisper_7ep_en * Add model 2023-09-14-bert_base_cased_finetuned_wallisian_whisper_8ep_en * Add model 2023-09-14-bert_base_cased_finetuned_wallisian_whisper_9ep_en * Add model 2023-09-14-bert_base_cased_finetuned_wallisian_whisper_10ep_en * Add model 2023-09-14-bert_base_cased_finetuned_wallisian_manual_1ep_en * Add model 2023-09-14-bert_base_uncased_finetuned_wallisian_manual_1ep_lower_en * Add model 2023-09-14-bert_base_cased_finetuned_wallisian_manual_2ep_en * Add model 2023-09-14-bert_base_uncased_finetuned_wallisian_manual_2ep_lower_en * Add model 2023-09-14-bert_base_cased_finetuned_wallisian_manual_3ep_en * Add model 2023-09-14-bert_base_uncased_finetuned_wallisian_manual_3ep_lower_en * Add model 2023-09-14-bert_base_cased_finetuned_wallisian_manual_4ep_en * Add model 2023-09-14-bert_base_uncased_finetuned_wallisian_manual_4ep_lower_en * Add model 2023-09-14-bert_base_cased_finetuned_wallisian_manual_5ep_en * Add model 2023-09-14-bert_base_uncased_finetuned_wallisian_manual_5ep_lower_en * Add model 2023-09-14-bert_base_cased_finetuned_wallisian_manual_6ep_en * Add model 2023-09-14-bert_base_uncased_finetuned_wallisian_manual_6ep_lower_en * Add model 2023-09-14-bert_base_cased_finetuned_wallisian_manual_7ep_en * Add model 2023-09-14-bert_base_uncased_finetuned_wallisian_manual_7ep_lower_en * Add model 2023-09-14-bert_base_cased_finetuned_wallisian_manual_8ep_en * Add model 2023-09-14-bert_base_uncased_finetuned_wallisian_manual_8ep_lower_en --------- Co-authored-by: ahmedlone127 * 2023-09-14-bert_base_cased_finetuned_wallisian_manual_9ep_en (#13982) * Add model 2023-09-14-bert_base_cased_finetuned_wallisian_manual_9ep_en * Add model 2023-09-14-bert_base_uncased_finetuned_wallisian_manual_9ep_lower_en * Add model 2023-09-14-bert_base_cased_finetuned_wallisian_manual_10ep_en * Add model 2023-09-14-bert_base_uncased_finetuned_wallisian_manual_10ep_lower_en * Add model 2023-09-14-bert_csic_en * Add model 2023-09-14-bert_pkdd_en * Add model 2023-09-14-bert_bgl_en * Add model 2023-09-14-bert_thunderbird_en * Add model 2023-09-14-bert_spirit_en * Add model 2023-09-14-bert_base_uncased_issues_128_ckandemir_en * Add model 2023-09-14-louribert_more_tokens_zahrabahmani61_en * Add model 2023-09-14-bert_base_uncased_finetuned_bert_auto2_en * Add model 2023-09-14-bert_base_arabertv02_finetuned_egyption_en * Add model 2023-09-14-bert_base_uncased_finetuned_bert_auto3_en * Add model 2023-09-14-bert_adaptation_martin_fierro_en * Add model 2023-09-14-bert_adaptation_vizwiz_en * Add model 2023-09-14-bert_adaptation_peppa_pig_en * Add model 2023-09-14-news_contrastive_pretrain_en * Add model 2023-09-14-dummy_model_sasikarn_en * Add model 2023-09-14-burmese_bert_model_en * Add model 2023-09-14-multilingual_bert_model_classiffication_xx * Add model 2023-09-14-wiki_contrastive_pretrain_en * Add model 2023-09-14-review_contrastive_pretrain_en * Add model 2023-09-14-bert_adaptation_referencias_german_vinos_en * Add model 2023-09-14-ar_mbertmodel_mberttok_en * Add model 2023-09-14-BERTUNAM_en * Add model 2023-09-14-ar_mbertmodel_monotok_adapter_en * Add model 2023-09-14-bert_large_cased_sigir_support_refute_no_label_40_2nd_test_LR10_8_8_en * Add model 2023-09-14-AethiQs_GemBERT_bertje_50k_en * Add model 2023-09-14-bert_base_uncased_issues_128_en * Add model 2023-09-14-ar_mbertmodel_monotok_en * Add model 2023-09-14-bert_large_cased_sigir_support_refute_no_label_40_2nd_test_LR10_8_9_en * Add model 2023-09-14-ar_monomodel_mberttok_en * Add model 2023-09-14-lsg16k_Italian_Legal_BERT_it * Add model 2023-09-14-ar_monomodel_monotok_en * Add model 2023-09-14-BiodivBERT_en * Add model 2023-09-14-AlephBertGimmel_10_epochs_en * Add model 2023-09-14-JavaBERT_uncased_en * Add model 2023-09-14-fi_mbertmodel_mberttok_en * Add model 2023-09-14-JavaBERT_en * Add model 2023-09-14-fi_mbertmodel_monotok_adapter_en * Add model 2023-09-14-AlephBertGimmel_20_epochs_en * Add model 2023-09-14-BERT_Base_CT_en * Add model 2023-09-14-fi_mbertmodel_monotok_en * Add model 2023-09-14-AlephBertGimmel_50_epochs_en * Add model 2023-09-14-fi_monomodel_mberttok_en * Add model 2023-09-14-BERT_Base_NLI_CT_en * Add model 2023-09-14-fi_monomodel_monotok_en * Add model 2023-09-14-BERT_Large_CT_en * Add model 2023-09-14-InLegalBERT_cbp_lkg_triples_finetuned_en * Add model 2023-09-14-distilbert_base_german_cased_de * Add model 2023-09-14-hf_distilbert_imdb_mlm_cosine_en * Add model 2023-09-14-distillbert_base_spanish_uncased_finetuned_spanish_corpus_en * Add model 2023-09-14-distilbert_base_german_cased_de * Add model 2023-09-14-hf_distilbert_imdb_mlm_cosine_en * Add model 2023-09-14-distillbert_base_spanish_uncased_finetuned_spanish_corpus_en * Add model 2023-09-14-distilbert_base_uncased_finetuned_imdb_en * Add model 2023-09-14-distilbert_base_uncased_finetuned2_imdb_en * Add model 2023-09-14-distilbert_base_uncased_finetuned_squad_d5716d28_en * Add model 2023-09-14-distilbert_v1_en * Add model 2023-09-14-distilbert_base_uncased_finetuned_imdb_accelerate_en * Add model 2023-09-14-distilbert_base_spanish_uncased_es * Add model 2023-09-14-distilbert_fa_zwnj_base_MLM_pquad_2_en * Add model 2023-09-14-distilbert_base_uncased_finetuned_imdb_accelerate_en * Add model 2023-09-14-google_Job_data_tuned_trial_1_en * Add model 2023-09-14-customer_data_tuned_trial_1_en * Add model 2023-09-14-distilbert_base_uncased_finetuned_recipe_accelerate_en * Add model 2023-09-14-distilbert_base_uncased_finetuned_CT_en * Add model 2023-09-14-BERT_Distil_CT_en * Add model 2023-09-14-distilbert_fa_zwnj_base_MLM_pquad_en * Add model 2023-09-14-dbert_finetuned_en * Add model 2023-09-14-mdistilbertV3.1_en * Add model 2023-09-14-marathi_distilbert_mr * Add model 2023-09-14-distilbert_base_uncased_finetuned_imdb_whole_word_en * Add model 2023-09-14-UKRI_DistilBERT_en * Add model 2023-09-14-first_try_4_en * Add model 2023-09-14-distilbert_base_25lang_cased_xx * Add model 2023-09-14-distilbert_base_uncased_finetuned_kintweetsE_en * Add model 2023-09-14-mlm_model_en * Add model 2023-09-14-debiasing_pre_trained_contextualised_embeddings_distil_bert_en * Add model 2023-09-14-distilbert_base_multilingual_cased_finetuned_kintweetsE_xx * Add model 2023-09-14-distilbert_base_german_cased_finetuned_amazon_reviews_de * Add model 2023-09-14-distilbert_base_uncased_finetuned_cvent_2022_en * Add model 2023-09-15-google_Job_data_tuned_trial_2_11_2_2022_en * Add model 2023-09-15-distilbert_base_en_ar_cased_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_cvent_2019_2022_en * Add model 2023-09-15-film20000distilbert_base_uncased_en * Add model 2023-09-14-DistilBert_Finetuned_SpMLM_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_homedepot_en * Add model 2023-09-14-Medicaldistilbert_en * Add model 2023-09-14-distilbert_base_uncased_finetuned_recipe_accelerate_1_en * Add model 2023-09-14-distilbert_base_uncased_finetuned_nitro_en * Add model 2023-09-14-remote_sensing_distilbert_cased_en * Add model 2023-09-15-distilbert_base_german_cased_de * Add model 2023-09-15-hf_distilbert_imdb_mlm_cosine_en * Add model 2023-09-14-BERT_Distil_NLI_CT_en * Add model 2023-09-14-distilbert_base_uncased_finetuned_domain_adaptation_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_squad_d5716d28_ysugawa_en * Add model 2023-09-15-distilbert_v1_en * Add model 2023-09-14-distilbert_base_uncased_linkedin_domain_adaptation_en * Add model 2023-09-14-distilbert_base_uncased_aisera_texts_v3_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_civi_cooments_accelerate_en * Add model 2023-09-14-Masked_Language_Model_en * Add model 2023-09-14-bertino_lsg_en * Add model 2023-09-14-distilbert_base_uncased_finetuned_speeches_en * Add model 2023-09-15-distilbert_base_en_bg_cased_en * Add model 2023-09-15-distillbert_base_spanish_uncased_finetuned_spanish_corpus_en * Add model 2023-09-14-distilbert_base_uncased_finetuned_mlm_2_en * Add model 2023-09-15-debiasing_pre_trained_contextualised_embeddings_distil_bert_en * Add model 2023-09-14-train_mask_language_model_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_sabby_en * Add model 2023-09-15-distilbert_base_uncased_finetuned2_imdb_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_ghost1_en * Add model 2023-09-14-distilbert_base_uncased_aisera_texts_en * Add model 2023-09-14-distilbert_embeddings_clinical_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_liquannan_en * Add model 2023-09-14-distilbert_base_uncased_finetuned_mlm_1_en --------- Co-authored-by: ahmedlone127 * 2023-09-15-distilbert_base_german_cased_de (#13984) * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_jaese_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_apatidar0_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_gg1313_en * Add model 2023-09-15-we4lkd_aml_distilbert_1921_2006_en * Add model 2023-09-15-distilbert_mlm_best_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_edraper88_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_thangvip_en * Add model 2023-09-15-distilbert_pubmed_mlm_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_game_accelerate_v2_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_reza93v_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_raphaelmerx_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_qianyu88_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_hemanth11_en * Add model 2023-09-15-erwt_year_southern_sotho_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_prasanthin_en * Add model 2023-09-15-distilabena_base_v2_asante_twi_uncased_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_squad_d5716d28_juancopi81_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_physhunter_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_outop_y_en * Add model 2023-09-15-eighteenth_century_distilbert_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_dave_sheets_en * Add model 2023-09-15-few_mask_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_test_headline_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_squad_d5716d28_peterhsu_en * Add model 2023-09-15-film20000distilbert_base_uncased_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_rd124_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_geolearner_en * Add model 2023-09-15-lsg_distilbert_base_uncased_4096_en * Add model 2023-09-15-distilbert_base_multilingual_cased_bulgarian_wikipedia_xx * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_qianyu88_en * Add model 2023-09-15-distilbert_base_uncased_mlm_tamil_local_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_jchhabra_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_dewa_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_kyle2023_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_caroline_betbeze_en * Add model 2023-09-15-we4lkd_aml_distilbert_1921_1997_en * Add model 2023-09-15-we4lkd_aml_distilbert_1921_1994_en * Add model 2023-09-15-we4lkd_aml_distilbert_1921_1966_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_recipe_accelerate_en * Add model 2023-09-15-we4lkd_aml_distilbert_1921_2008_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_jake777_en * Add model 2023-09-15-we4lkd_aml_distilbert_1921_1988_en * Add model 2023-09-15-we4lkd_aml_distilbert_1921_2021_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_feeeper_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_mchalek_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_v2_accelerate_en * Add model 2023-09-15-500_sdb_tbb_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_ccnews_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_wjbmattingly_en * Add model 2023-09-15-marathi_distilbert_pretrained_mr * Add model 2023-09-15-remote_sensing_distilbert_cased_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_guidoivetta_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_solver_paul_en * Add model 2023-09-15-inisw08_distilbert_mlm_lion_32bit_test_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_brenton_en * Add model 2023-09-15-20split_dataset_version1_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_v2_francesco_a_en * Add model 2023-09-15-mtl_distilbert_base_uncased_en * Add model 2023-09-15-we4lkd_aml_distilbert_1921_1985_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_rushikesh_en * Add model 2023-09-15-we4lkd_aml_distilbert_1921_1991_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_shadowtwin41_en * Add model 2023-09-15-aave_distil_bert_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_eitanli_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_waynechiu_en * Add model 2023-09-15-distilbert_add_pre_training_dim_96_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_rap_lyrics_v1_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_iven5880_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_vsrinivas_en * Add model 2023-09-15-we4lkd_aml_distilbert_1921_2000_en * Add model 2023-09-15-burmese_finetuned_distilbert_portuguese_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_tweet_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_discord_en * Add model 2023-09-15-distilbert_base_english_chinese_hindi_cased_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_junchengding_en * Add model 2023-09-15-distilbert_base_uncased_sparse_90_unstructured_pruneofa_en * Add model 2023-09-15-tod_distilbert_jnt_v1_en * Add model 2023-09-15-distilbert_embeddings_clinical_en * Add model 2023-09-15-absa_with_maskedlm_finetuned_sentihood_en * Add model 2023-09-15-distilbert_perigon_200k_en * Add model 2023-09-15-distilbert_base_uncased_wholewordmasking_finetuned_imdb_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_sonali_behera_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_squad_d5716d28_nicolacandussi_en * Add model 2023-09-15-distilbert_base_english_french_spanish_german_chinese_cased_en * Add model 2023-09-15-first_try_4_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_tanvirkhan_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_golightly_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_harshseth_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_im_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_tkoyama_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_caroline_betbeze_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_vanhoan_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_talha185_en * Add model 2023-09-15-distilbert_ravenk_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_arthuerwang_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_cnn_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_robkayinto_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_lokeshsoni2801_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_rdvdsn_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_squad_d5716d28_dchung117_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_mholi_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_arunadiraju_en * Add model 2023-09-15-distilbert_splade_en * Add model 2023-09-15-hinglish_distilbert_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_hina_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_amazon_review_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_mascariddu8_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_squad_d5716d28_mbateman_en * Add model 2023-09-15-distilbert_base_english_french_chinese_japanese_vietnamese_cased_en * Add model 2023-09-15-we4lkd_aml_distilbert_1921_2013_en * Add model 2023-09-15-distilbert_base_english_thai_cased_en * Add model 2023-09-15-distilbert_base_english_japanese_cased_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_sgasparorippa_en * Add model 2023-09-15-distilabena_base_v2_akuapem_twi_cased_en * Add model 2023-09-15-experiment_en * Add model 2023-09-15-flang_distilbert_en * Add model 2023-09-15-bert_base_uncased_finetuned_imdb_accelerate_en * Add model 2023-09-15-we4lkd_aml_distilbert_1921_2002_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_outop_j_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_snousias_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_anikaai_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_squad_d5716d28_suzuki0829_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_allocation_en * Add model 2023-09-15-we4lkd_aml_distilbert_1921_1998_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_himani_auto_en * Add model 2023-09-15-bert_tuned_trial_20_12_2022_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_dieexbr_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_squad_d5716d28_sophon_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_himani_auto_text_gen_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_squad_d5716d28_nugget00_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_yangwooko_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_cchychen_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_squad_d5716d28_gautam1989_en * Add model 2023-09-15-distilbert_embeddings_base_uncased_finetuned_imdb_accelerate_en * Add model 2023-09-15-bertino_lsg_en * Add model 2023-09-15-distilbert_base_spanish_uncased_model_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_cssupport_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_terps_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_vanhoan_en * Add model 2023-09-15-fine_tuned_distilbert_nosql_injection_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_elggman_en * Add model 2023-09-15-sae_distilbert_base_uncased_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_squad_d5716d28_iotengtr_en * Add model 2023-09-15-distilbert_base_uncased_malayalam_arxiv_papers_en * Add model 2023-09-15-clr_pretrained_distilbert_base_uncased_en * Add model 2023-09-15-we4lkd_aml_distilbert_1921_2020_en * Add model 2023-09-15-we4lkd_aml_distilbert_1921_2011_en * Add model 2023-09-15-distilbert_base_uncased_imdb_distilbert_en * Add model 2023-09-15-inisw08_distilbert_mlm_adamw_torch_fused_en * Add model 2023-09-15-distilbert_mlm_500k_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_eusojk_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_crypto_en * Add model 2023-09-15-spladex_zs_en * Add model 2023-09-15-hf_distilbert_imdb_mlm_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_fadliaulawi_en * Add model 2023-09-15-distilabena_base_asante_twi_uncased_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_hilariooliveira_en * Add model 2023-09-15-distilbert_classification_eplorer_en * Add model 2023-09-15-distilbert_hemingway_sar_en * Add model 2023-09-15-distilbert_base_english_lithuanian_cased_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_himani_m_en * Add model 2023-09-15-splade_v2_max_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_squad_d5716d28_sgr23_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_peterhsu_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_squad_d5716d28_shadowtwin41_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_evincent18_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_fetch_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_cleandata_en * Add model 2023-09-15-distilbert_base_multilingual_cased_finetuned_kintweetse_xx * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_tlapusan_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_tsobolev_en * Add model 2023-09-15-dummy_model_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_himani_auto_gen_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_surjray_en * Add model 2023-09-15-we4lkd_aml_distilbert_1921_2022_en * Add model 2023-09-15-clinical_bert_finetuned_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_thangvip_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_squad_d5716d28_coreyabs_db_en * Add model 2023-09-15-distilbert_base_uncased_mask_finetuned_imdb_v1_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_spasis_en * Add model 2023-09-15-erwt_year_en * Add model 2023-09-15-bertino_it * Add model 2023-09-15-distilbert_base_uncased_finetuned_himani_auto_textgeneration_en * Add model 2023-09-15-distilbert_base_uncased_imdb_accelerate_en * Add model 2023-09-15-film20000film20000distilbert_base_uncased_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_fadliaulawi_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_ttmusic_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_squad_d5716d28_lakecrimsonn_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_huggingface_course_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_coreyabs_db_en * Add model 2023-09-15-dbert_finetuned_g_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_cl_wood_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_raulgdp_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_jwchung_en * Add model 2023-09-15-distilbert_base_uncased_sparse_80_1x4_block_pruneofa_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_averageandyyy_en * Add model 2023-09-15-test_text_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_averageandyyy_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_francesc_en * Add model 2023-09-15-distilbert_base_turkish_cased_offensive_mlm_tr * Add model 2023-09-15-distilbert_base_english_french_spanish_portuguese_italian_cased_xx * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_techtank_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_cvent_2019_2022_en * Add model 2023-09-15-distilbert_base_uncased_mlm_scirepeval_fos_chemistry_en * Add model 2023-09-15-100_sdb_tbb_en * Add model 2023-09-15-we4lkd_aml_distilbert_1921_2009_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_yuto01_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_thetaphipsi_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_rugo_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_squad_d5716d28_guoguo_en * Add model 2023-09-15-yolochess_mlm_azure_cloud_35_en * Add model 2023-09-15-we4lkd_aml_distilbert_1921_2019_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_ryanlai_en * Add model 2023-09-15-distilbert_embeddings_base_uncased_continued_training_medqa_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_squad_d5716d28_luzimu_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_thutrang_en * Add model 2023-09-15-javanese_distilbert_small_jv * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_johnyyhk_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_finetuned_imdb_chenyanjin_en * Add model 2023-09-15-spladex_tt_spanish_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_gtxygyzb_en * Add model 2023-09-15-erwt_year_masked_75_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_andrewr_en * Add model 2023-09-15-distilbert_base_english_urdu_cased_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_sungchun71_en * Add model 2023-09-15-we4lkd_aml_distilbert_1921_1992_en * Add model 2023-09-15-pt_distilbert_base_en * Add model 2023-09-15-distilbert_base_english_french_german_cased_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_mlm_accelerate_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_nugget00_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_tux_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_squad_d5716d28_gostrive_en * Add model 2023-09-15-we4lkd_aml_distilbert_1921_1965_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_renyulin_en * Add model 2023-09-15-we4lkd_aml_distilbert_1921_2016_en * Add model 2023-09-15-distilbert_finetuned_spmlm_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_dipika09_en * Add model 2023-09-15-distilbert_mlm_750k_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_golightly_en * Add model 2023-09-15-distilbert_base_english_french_spanish_cased_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_minye819_en * Add model 2023-09-15-distilbert_base_english_russian_cased_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_ryanlai_en * Add model 2023-09-15-kaz_legal_distilbert_legal_corpus_312818008_words_4.945454545454545_en * Add model 2023-09-15-distilbert_base_indonesian_id * Add model 2023-09-15-we4lkd_aml_distilbert_1921_1977_en * Add model 2023-09-15-inisw08_distilbert_mlm_adamw_torch_0608_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_jjinbbangman_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_imdb_accelerate_dmlea_en * Add model 2023-09-15-distilbert_base_uncased_finetuned_himani_auto_text_en --------- Co-authored-by: ahmedlone127 * 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_hate_word_swapping_synonym_4_en (#13992) * Add model 2023-09-18-m3_experiment_albert_base_v2_rct_sample_word_swapping_embedding_1_en * Add model 2023-09-18-m3_experiment_albert_base_v2_sciie_word_swapping_embedding_3_en * Add model 2023-09-18-m3_experiment_albert_base_v2_rct_sample_eda_2_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_irony_eda_3_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_emotion_eda_1_en * Add model 2023-09-18-m3_experiment_albert_base_v2_rct_sample_add_v2_en * Add model 2023-09-18-m3_experiment_albert_base_v2_rct_sample_word_swapping_random_0_en * Add model 2023-09-18-albert_base_v1_mnli_en * Add model 2023-09-18-albert_dnd_intents_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_irony_word_swapping_synonym_0_en * Add model 2023-09-18-albert_large_v2_cola_en * Add model 2023-09-18-albert_base_vitaminc_flagging_en * Add model 2023-09-18-sst2_eda_albert_en * Add model 2023-09-18-m3_experiment_albert_base_v2_sciie_add_v3_greedy_en * Add model 2023-09-18-albert_base_vitaminc_mnli_en * Add model 2023-09-18-albert_large_v2_rte_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_emotion_add_v3_greedy_en * Add model 2023-09-18-trecdl22_crossencoder_albert_en * Add model 2023-09-18-m3_experiment_albert_base_v2_rct_sample_word_swapping_embedding_4_en * Add model 2023-09-18-albert_xlarge_vitaminc_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_irony_word_swapping_synonym_3_en * Add model 2023-09-18-m3_experiment_albert_base_v2_chemprot_word_swapping_synonym_2_en * Add model 2023-09-18-m3_experiment_albert_base_v2_chemprot_word_swapping_random_4_en * Add model 2023-09-18-m3_experiment_albert_base_v2_chemprot_vanilla_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_irony_word_swapping_synonym_4_en * Add model 2023-09-18-m3_experiment_albert_base_v2_rct_sample_vanilla_en * Add model 2023-09-18-m3_experiment_albert_base_v2_sciie_word_swapping_random_1_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_irony_word_swapping_embedding_0_en * Add model 2023-09-18-albert_base_v2_hoax_classifier_v1_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_irony_vanilla_en * Add model 2023-09-18-albert_base_v2_mbti_classification_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_irony_word_swapping_embedding_1_en * Add model 2023-09-18-albert_xxlarge_v2_hoax_classifier_v1_en * Add model 2023-09-18-m3_experiment_albert_base_v2_citation_intent_word_swapping_synonym_2_en * Add model 2023-09-18-albert_large_v2_sst2_en * Add model 2023-09-18-albert_xxlarge_v2_snli_mnli_fever_anli_r1_r2_r3_nli_en * Add model 2023-09-18-autotrain_security_text_classification_albert_688320769_en * Add model 2023-09-18-m3_experiment_albert_base_v2_citation_intent_word_swapping_synonym_4_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_irony_word_swapping_embedding_4_en * Add model 2023-09-18-albert_base_fever_claim_related_en * Add model 2023-09-18-albert_xxlarge_v2_hoax_classifier_def_v1_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_irony_word_swapping_random_1_en * Add model 2023-09-18-m3_experiment_albert_base_v2_chemprot_word_swapping_synonym_3_en * Add model 2023-09-18-m3_experiment_albert_base_v2_citation_intent_vanilla_en * Add model 2023-09-18-m3_experiment_albert_base_v2_sciie_word_swapping_random_2_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_irony_word_swapping_random_4_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_hate_word_swapping_synonym_0_en * Add model 2023-09-18-m3_experiment_albert_base_v2_chemprot_eda_0_en * Add model 2023-09-18-yhi_message_type_paraphrase_albert_small_v2_en * Add model 2023-09-18-m3_experiment_albert_base_v2_rct_sample_word_swapping_synonym_4_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_hate_word_swapping_random_1_en * Add model 2023-09-18-m3_experiment_albert_base_v2_sciie_word_swapping_random_3_en * Add model 2023-09-18-m3_experiment_albert_base_v2_chemprot_word_swapping_random_3_en * Add model 2023-09-18-m3_experiment_albert_base_v2_amcd_eda_4_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_hate_word_swapping_random_4_en * Add model 2023-09-18-m3_experiment_albert_base_v2_sciie_word_swapping_synonym_1_en * Add model 2023-09-18-m3_experiment_albert_base_v2_chemprot_eda_4_en * Add model 2023-09-18-m3_experiment_albert_base_v2_citation_intent_word_swapping_random_0_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_irony_word_swapping_random_0_en * Add model 2023-09-18-m3_experiment_albert_base_v2_citation_intent_word_swapping_random_1_en * Add model 2023-09-18-nosql_identifier_albert_en * Add model 2023-09-18-albert_base_v2_hoax_classifier_fulltext_v1_en * Add model 2023-09-18-m3_experiment_albert_base_v2_citation_intent_word_swapping_random_4_en * Add model 2023-09-18-m3_experiment_albert_base_v2_sciie_vanilla_en * Add model 2023-09-18-m3_experiment_albert_base_v2_rct_sample_word_swapping_synonym_3_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_hate_word_swapping_synonym_1_en * Add model 2023-09-18-m3_experiment_albert_base_v2_citation_intent_word_swapping_synonym_1_en * Add model 2023-09-18-m3_experiment_albert_base_v2_chemprot_word_swapping_synonym_1_en * Add model 2023-09-18-m3_experiment_albert_base_v2_rct_sample_eda_4_en * Add model 2023-09-18-m3_experiment_albert_base_v2_citation_intent_add_v5_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_irony_eda_2_en * Add model 2023-09-18-m3_experiment_albert_base_v2_sciie_add_v3_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_irony_word_swapping_synonym_2_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_hate_word_swapping_random_2_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_emotion_word_swapping_synonym_4_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_emotion_add_v5_en * Add model 2023-09-18-albert_base_v2_sts_b_en * Add model 2023-09-18-albert_base_v2_rotten_tomatoes_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_irony_word_swapping_random_3_en * Add model 2023-09-18-albert_base_v2_yelp_polarity_en * Add model 2023-09-18-m3_experiment_albert_base_v2_rct_sample_word_swapping_embedding_3_en * Add model 2023-09-18-m3_experiment_albert_base_v2_citation_intent_add_v2_en * Add model 2023-09-18-m3_experiment_albert_base_v2_sciie_word_swapping_random_4_en * Add model 2023-09-18-m3_experiment_albert_base_v2_sciie_eda_4_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_hate_eda_4_en * Add model 2023-09-18-m3_experiment_albert_base_v2_citation_intent_add_v3_greedy_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_emotion_word_swapping_random_0_en * Add model 2023-09-18-m3_experiment_albert_base_v2_amcd_word_swapping_synonym_3_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_emotion_word_swapping_embedding_3_en * Add model 2023-09-18-m3_experiment_albert_base_v2_amcd_word_swapping_random_3_en * Add model 2023-09-18-albert_base_v2_toxicity_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_hate_word_swapping_random_3_en * Add model 2023-09-18-m3_experiment_albert_base_v2_sciie_word_swapping_embedding_4_en * Add model 2023-09-18-m3_experiment_albert_base_v2_chemprot_back_translation_en * Add model 2023-09-18-albert_base_v2_snli_en * Add model 2023-09-18-m3_experiment_albert_base_v2_citation_intent_eda_1_en * Add model 2023-09-18-m3_experiment_albert_base_v2_citation_intent_word_swapping_random_3_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_hate_add_v3_en * Add model 2023-09-18-albert_large_v2_cls_sst2_en * Add model 2023-09-18-mnli_albert_base_v2_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_hate_add_v5_en * Add model 2023-09-18-m3_experiment_albert_base_v2_amcd_add_v3_greedy_en * Add model 2023-09-18-albert_base_mnli_en * Add model 2023-09-18-m3_experiment_albert_base_v2_chemprot_word_swapping_random_0_en * Add model 2023-09-18-m3_experiment_albert_base_v2_amcd_word_swapping_synonym_2_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_hate_eda_1_en * Add model 2023-09-18-albert_base_v2_finetuned_filtered_0609_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_hate_add_v2_en * Add model 2023-09-18-m3_experiment_albert_base_v2_citation_intent_word_swapping_synonym_0_en * Add model 2023-09-18-m3_experiment_albert_base_v2_amcd_word_swapping_synonym_4_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_irony_word_swapping_random_2_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_emotion_word_swapping_synonym_0_en * Add model 2023-09-18-m3_experiment_albert_base_v2_amcd_word_swapping_synonym_1_en * Add model 2023-09-18-albert_offensive_lm_tapt_finetuned_en * Add model 2023-09-18-albert_small_kor_cross_encoder_v1_ko * Add model 2023-09-18-m3_experiment_albert_base_v2_rct_sample_word_swapping_random_1_en * Add model 2023-09-18-m3_experiment_albert_base_v2_rct_sample_eda_3_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_hate_eda_3_en * Add model 2023-09-18-m3_experiment_albert_base_v2_amcd_eda_3_en * Add model 2023-09-18-m3_experiment_albert_base_v2_rct_sample_word_swapping_embedding_0_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_irony_eda_0_en * Add model 2023-09-18-m3_experiment_albert_base_v2_rct_sample_word_swapping_synonym_1_en * Add model 2023-09-18-albert_goodnotes_reddit_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_irony_word_swapping_embedding_2_en * Add model 2023-09-18-m3_experiment_albert_base_v2_sciie_back_translation_en * Add model 2023-09-18-m3_experiment_albert_base_v2_chemprot_word_swapping_embedding_0_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_irony_word_swapping_synonym_1_en * Add model 2023-09-18-m3_experiment_albert_base_v2_sciie_word_swapping_random_0_en * Add model 2023-09-18-m3_experiment_albert_base_v2_chemprot_word_swapping_embedding_2_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_irony_add_v4_en * Add model 2023-09-18-m3_experiment_albert_base_v2_amcd_back_translation_en * Add model 2023-09-18-albert_base_vitaminc_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_hate_word_swapping_random_0_en * Add model 2023-09-18-m3_experiment_albert_base_v2_sciie_eda_2_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_hate_add_v3_greedy_en * Add model 2023-09-18-m3_experiment_albert_base_v2_amcd_add_v4_en * Add model 2023-09-18-m3_experiment_albert_base_v2_amcd_word_swapping_random_1_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_emotion_add_v4_en * Add model 2023-09-18-m3_experiment_albert_base_v2_amcd_vanilla_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_emotion_word_swapping_embedding_0_en * Add model 2023-09-18-albert_base_v2_mnli_tehrannlp_en * Add model 2023-09-18-m3_experiment_albert_base_v2_amcd_word_swapping_random_2_en * Add model 2023-09-18-m3_experiment_albert_base_v2_rct_sample_word_swapping_synonym_2_en * Add model 2023-09-18-albert_base_v2_imdb_textattack_en * Add model 2023-09-18-m3_experiment_albert_base_v2_citation_intent_word_swapping_synonym_3_en * Add model 2023-09-18-albert_base_v2_wnli_en * Add model 2023-09-18-m3_experiment_albert_base_v2_citation_intent_eda_0_en * Add model 2023-09-18-m3_experiment_albert_base_v2_sciie_eda_0_en * Add model 2023-09-18-m3_experiment_albert_base_v2_citation_intent_eda_4_en * Add model 2023-09-18-m3_experiment_albert_base_v2_rct_sample_word_swapping_random_2_en * Add model 2023-09-18-albert_large_v2_hoax_classifier_def_v1_en * Add model 2023-09-18-albert_large_v2_qqp_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_emotion_word_swapping_synonym_1_en * Add model 2023-09-18-albert_tiny_spanish_fakenews_en * Add model 2023-09-18-m3_experiment_albert_base_v2_rct_sample_add_v5_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_hate_word_swapping_embedding_1_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_hate_vanilla_en * Add model 2023-09-18-m3_experiment_albert_base_v2_citation_intent_eda_3_en * Add model 2023-09-18-albert_base_v2_sst_2_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_hate_word_swapping_synonym_3_en * Add model 2023-09-18-albert_for_math_arabic_base_ft_en * Add model 2023-09-18-albert_base_v2_mnli_prajjwal1_en * Add model 2023-09-18-m3_experiment_albert_base_v2_chemprot_add_v3_greedy_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_irony_add_v3_greedy_en * Add model 2023-09-18-m3_experiment_albert_base_v2_rct_sample_add_v3_greedy_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_emotion_vanilla_en * Add model 2023-09-18-m3_experiment_albert_base_v2_amcd_word_swapping_embedding_1_en * Add model 2023-09-18-albert_model_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_emotion_word_swapping_synonym_3_en * Add model 2023-09-18-m3_experiment_albert_base_v2_chemprot_word_swapping_synonym_4_en * Add model 2023-09-18-m3_experiment_albert_base_v2_citation_intent_back_translation_en * Add model 2023-09-18-m3_experiment_albert_base_v2_chemprot_eda_1_en * Add model 2023-09-18-m3_experiment_albert_base_v2_chemprot_eda_3_en * Add model 2023-09-18-m3_experiment_albert_base_v2_amcd_word_swapping_embedding_2_en * Add model 2023-09-18-m3_experiment_albert_base_v2_rct_sample_back_translation_en * Add model 2023-09-18-albert_base_v2_tweet_about_disaster_or_not_en * Add model 2023-09-18-m3_experiment_albert_base_v2_rct_sample_word_swapping_synonym_0_en * Add model 2023-09-18-albert_base_quora_classifier_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_emotion_back_translation_en * Add model 2023-09-18-m3_experiment_albert_base_v2_citation_intent_word_swapping_random_2_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_hate_word_swapping_synonym_2_en * Add model 2023-09-18-albert_base_vitaminc_wnei_fever_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_hate_add_v4_en * Add model 2023-09-18-albert_base_v2_qqp_en * Add model 2023-09-18-albert_xlarge_vitaminc_fever_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_hate_word_swapping_embedding_0_en * Add model 2023-09-18-m3_experiment_albert_base_v2_rct_sample_word_swapping_random_4_en * Add model 2023-09-18-albert_base_v2_hoax_classifier_def_v1_en * Add model 2023-09-18-m3_experiment_albert_base_v2_chemprot_word_swapping_synonym_0_en * Add model 2023-09-18-albert_large_v2_mnli_en * Add model 2023-09-18-albert_base_v2_finetuned_mrpc_en * Add model 2023-09-18-albert_large_v2_stsb_en * Add model 2023-09-18-m3_experiment_albert_base_v2_rct_sample_word_swapping_embedding_2_en * Add model 2023-09-18-albert_large_v2_mrpc_en * Add model 2023-09-18-m3_experiment_albert_base_v2_citation_intent_eda_2_en * Add model 2023-09-18-albert_large_v2_qnli_en * Add model 2023-09-18-m3_experiment_albert_base_v2_amcd_add_v5_en * Add model 2023-09-18-albert_base_v2_ag_news_en * Add model 2023-09-18-m3_experiment_albert_base_v2_sciie_add_v2_en * Add model 2023-09-18-albert_base_vitaminc_fever_en * Add model 2023-09-18-m3_experiment_albert_base_v2_chemprot_word_swapping_embedding_1_en * Add model 2023-09-18-m3_experiment_albert_base_v2_sciie_word_swapping_embedding_0_en * Add model 2023-09-18-m3_experiment_albert_base_v2_tweet_eval_irony_word_swapping_embedding_3_en * Add model 2023-09-18-albert_xlarge_vitaminc_mnli_en * Add model 2023-09-18-albert_xlarge_arabic_finetuned_emotion_aetd_en * Add model 2023-09-18-m3_experiment_albert_base_v2_chemprot_eda_2_en * Add model 2023-09-18-m3_experiment_albert_base_v2_sciie_word_swapping_synonym_4_en * Add model 2023-09-19-albert_persian_farsi_zwnj_base_v2_ner_fa * Add model 2023-09-19-albert_persian_farsi_zwnj_base_v2_ner_fa * Add model 2023-09-19-lodosalberttr_en * Add model 2023-09-19-albert_large_v2_ner_wnut_17_en * Add model 2023-09-19-albert_persian_farsi_base_v2_ner_arman_fa * Add model 2023-09-19-albert_large_v2_ner_conll2003_en * Add model 2023-09-19-albert_persian_farsi_base_v2_ner_peyma_fa * Add model 2023-09-19-albert_base_v2_en * Add model 2023-09-19-albert_large_v2_ner_wikiann_en * Add model 2023-09-19-tiny_albert_en * Add model 2023-09-19-albert_for_question_answering_en * Add model 2023-09-19-albert_xlarge_squad_finetuned_en * Add model 2023-09-19-albert_xxlarge_squad_finetuned_en * Add model 2023-09-19-albert_qa_squad_slp_en * Add model 2023-09-19-albert_base_finetuned_recipeqa_modified_en * Add model 2023-09-19-albert_qa_slp_en * Add model 2023-09-19-albert_v2_base_finetuned_recipeqa_modified_en * Add model 2023-09-19-albert_base_v2_finetuned_squad_attempt_1_en * Add model 2023-09-19-m_albert_qa_model_en * Add model 2023-09-19-albert_large_v2_spoken_squad_en * Add model 2023-09-19-albert_qa_xxlargev1_squad2_512_en * Add model 2023-09-19-albert_qa_xxlarge_v2_squad2_covid_deepset_en * Add model 2023-09-19-albert_qa_xlarge_finetuned_en * Add model 2023-09-19-albert_qa_cs224n_squad2.0_base_v2_en * Add model 2023-09-19-albert_xl_v2_finetuned_squad_en * Add model 2023-09-19-albert_qa_cs224n_squad2.0_large_v2_en * Add model 2023-09-19-albert_xxl_v2_finetuned_squad_en * Add model 2023-09-19-albert_qa_cs224n_squad2.0_xxlarge_v1_en * Add model 2023-09-19-albert_persian_farsi_base_v2_finetuned_squad_en * Add model 2023-09-19-albert_persian_farsi_base_v2_pquad_en * Add model 2023-09-19-albert_qa_xlarge_v2_squad_v2_en * Add model 2023-09-19-albert_persian_farsi_base_v2_persian_qa_en * Add model 2023-09-19-albert_qa_base_v2_squad_en * Add model 2023-09-19-albert_persian_farsi_base_v2_parsquad_en * Add model 2023-09-19-albert_persian_farsi_base_v2_pquad_and_persian_qa_en * Add model 2023-09-19-albert_qa_xxlarge_v2_squad2_en * Add model 2023-09-19-albert_qa_nlpunibo_en * Add model 2023-09-19-albert_qa_xxlarge_v1_finetuned_squad2_en * Add model 2023-09-19-albert_qa_xxlarge_tweetqa_en * Add model 2023-09-19-albert_base_qa_squad2_en * Add model 2023-09-20-albert_qa_biom_xxlarge_squad2_en * Add model 2023-09-20-albert_qa_ai_club_inductions_21_nlp_en * Add model 2023-09-20-albert_qa_qa_1e_en --------- Co-authored-by: ahmedlone127 * Add model 2023-09-18-AtgxRobertaBaseSquad2_en (#13988) Co-authored-by: LIN-Yu-Ting * 2023-09-20-image_captioning_vit_gpt2_en (#13999) * Add model 2023-09-20-image_captioning_vit_gpt2_en * Update 2023-09-20-image_captioning_vit_gpt2_en.md make sure spark_version is 3.0 --------- Co-authored-by: DevinTDHa Co-authored-by: Maziyar Panahi * 2023-09-21-multilingual_e5_base_xx (#14002) * Add model 2023-09-21-multilingual_e5_base_xx * Add model 2023-09-21-multilingual_e5_large_xx * Add model 2023-09-21-multilingual_e5_small_xx --------- Co-authored-by: ahmedlone127 * 2023-09-22-bert_embeddings_frpile_gpl_en (#14003) * Add model 2023-09-22-bert_embeddings_frpile_gpl_en * Add model 2023-09-22-bert_embeddings_retromae_beir_en * Add model 2023-09-22-bert_embeddings_retromae_msmarco_finetune_en * Add model 2023-09-22-bert_embeddings_allnli_gronlp_base_dutch_cased_nl * Add model 2023-09-22-bert_embeddings_bge_base_en * Add model 2023-09-22-bert_embeddings_bge_large_en * Add model 2023-09-22-bert_embeddings_bge_small_en * Add model 2023-09-22-bert_embeddings_bi_encoder_msmarco_base_german_de * Add model 2023-09-22-bert_embeddings_claif_base_en * Add model 2023-09-22-bert_embeddings_claif_scaled_base_en --------- Co-authored-by: SKocer * 2023-10-17-asr_whisper_kannada_base_kn (#14030) * Add model 2023-10-17-asr_whisper_kannada_base_kn * Add model 2023-10-17-asr_whisper_kannada_base_pipeline_kn * Add model 2023-10-17-asr_whisper_small_swe_davidt123_en * Add model 2023-10-17-asr_whisper_tiny_xx * Add model 2023-10-17-asr_whisper_small_swe_davidt123_pipeline_en * Add model 2023-10-17-asr_whisper_small_tonga_zambia_en * Add model 2023-10-17-asr_whisper_tiny_pipeline_xx * Add model 2023-10-17-asr_whisper_small_tonga_zambia_pipeline_en * Add model 2023-10-17-asr_whisper_small_swahili_pplantinga_sw * Add model 2023-10-17-asr_whisper_small_swahili_pplantinga_pipeline_sw * Add model 2023-10-17-asr_whisper_base_xx * Add model 2023-10-17-asr_whisper_base_pipeline_xx * Add model 2023-10-17-asr_whisper_small_greek_el * Add model 2023-10-17-asr_whisper_small_greek_pipeline_el * Add model 2023-10-17-asr_whisper_small_se2_en * Add model 2023-10-17-asr_whisper_small_se2_pipeline_en * Add model 2023-10-17-asr_whisper_small_xx * Add model 2023-10-17-asr_whisper_small_pipeline_xx * Add model 2023-10-17-asr_whisper_small_allsnr_de * Add model 2023-10-17-asr_whisper_base_bulgarian_l_en * Add model 2023-10-17-asr_whisper_base_bulgarian_l_pipeline_en * Add model 2023-10-17-asr_whisper_small_czech_cv11_cs * Add model 2023-10-17-asr_whisper_small_czech_cv11_pipeline_cs * Add model 2023-10-17-asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized_fr * Add model 2023-10-17-asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized_pipeline_fr * Add model 2023-10-17-asr_whisper_tswana_greek_modern_e1_el * Add model 2023-10-17-asr_whisper_tswana_greek_modern_e1_pipeline_el * Add model 2023-10-17-asr_whisper_small_thai_napatswift_th * Add model 2023-10-17-asr_whisper_small_thai_napatswift_pipeline_th * Add model 2023-10-17-asr_whisper_small_mongolian_1_mn * Add model 2023-10-17-asr_whisper_small_mongolian_1_pipeline_mn * Add model 2023-10-17-asr_whisper_tiny_bulgarian_l_bg * Add model 2023-10-17-asr_whisper_tiny_bulgarian_l_pipeline_bg * Add model 2023-10-17-asr_whisper_tiny_english_pipeline_en * Add model 2023-10-17-asr_whisper_small_telugu_146h_te * Add model 2023-10-17-asr_whisper_tiny_english_en * Add model 2023-10-17-asr_whisper_small_telugu_146h_pipeline_te * Add model 2023-10-17-asr_whisper_base_english_en * Add model 2023-10-17-asr_whisper_base_english_pipeline_en * Add model 2023-10-17-asr_whisper_small_telugu_openslr_en * Add model 2023-10-17-asr_whisper_small_telugu_openslr_pipeline_en * Add model 2023-10-17-asr_whisper_kannada_small_kn * Add model 2023-10-17-asr_whisper_kannada_small_pipeline_kn * Add model 2023-10-17-asr_whisper_telugu_tiny_te * Add model 2023-10-17-asr_whisper_telugu_tiny_pipeline_te * Add model 2023-10-17-asr_whisper_small_ukrainian_uk * Add model 2023-10-17-asr_whisper_small_mongolian_2_en * Add model 2023-10-17-asr_whisper_small_ukrainian_pipeline_uk * Add model 2023-10-17-asr_whisper_small_mongolian_2_pipeline_en * Add model 2023-10-17-asr_whisper_small_english_en * Add model 2023-10-17-asr_whisper_small_english_pipeline_en * Add model 2023-10-17-asr_whisper_small_italian_3_it * Add model 2023-10-17-asr_whisper_small_italian_3_pipeline_it * Add model 2023-10-17-asr_whisper_tiny_pashto_en * Add model 2023-10-17-asr_whisper_tiny_pashto_pipeline_en * Add model 2023-10-18-asr_whisper_tiny_german_en * Add model 2023-10-18-asr_whisper_tiny_german_pipeline_en * Add model 2023-10-18-asr_whisper_small_chinese_zh * Add model 2023-10-18-asr_whisper_small_chinese_pipeline_zh * Add model 2023-10-18-asr_whisper_small_hindi_shripadbhat_hi * Add model 2023-10-18-asr_whisper_small_hindi_shripadbhat_pipeline_hi * Add model 2023-10-18-asr_whisper_small_german_en * Add model 2023-10-18-asr_whisper_small_german_pipeline_en * Add model 2023-10-18-asr_whisper_small_chinese_hk_en * Add model 2023-10-18-asr_whisper_base_bengali_trans_xx * Add model 2023-10-18-asr_whisper_base_bengali_trans_pipeline_xx * Add model 2023-10-18-asr_whisper_small_chinese_hk_pipeline_en * Add model 2023-10-18-asr_whisper_persian_farsi_en * Add model 2023-10-18-asr_whisper_persian_farsi_pipeline_en * Add model 2023-10-18-asr_whisper_small_japanese_jakeyoo_ja * Add model 2023-10-18-asr_whisper_small_japanese_jakeyoo_pipeline_ja * Add model 2023-10-18-asr_whisper_samoan_farsipal_e5_el * Add model 2023-10-18-asr_whisper_samoan_farsipal_e5_pipeline_el * Add model 2023-10-18-asr_whisper_small_hindi_norwegian_tensorboard_pipeline_hi * Add model 2023-10-18-asr_whisper_small_hindi_norwegian_tensorboard_hi * Add model 2023-10-18-asr_whisper_tiny_tamil_example_ta * Add model 2023-10-18-asr_whisper_tiny_tamil_example_pipeline_ta * Add model 2023-10-18-asr_whisper_tiny_tgl_en * Add model 2023-10-18-asr_whisper_tiny_tgl_pipeline_en * Add model 2023-10-18-asr_whisper_tiny_xx * Add model 2023-10-18-asr_whisper_tiny_pipeline_xx * Add model 2023-10-18-asr_whisper_base_xx * Add model 2023-10-18-asr_whisper_base_pipeline_xx * Add model 2023-10-18-asr_whisper_small_tatar_tt * Add model 2023-10-18-asr_whisper_small_tatar_pipeline_tt * Add model 2023-10-18-asr_whisper_small_portuguese_yapeng_en * Add model 2023-10-18-asr_whisper_small_portuguese_yapeng_pipeline_en * Add model 2023-10-18-asr_whisper_small_finnish_15k_samples_fi * Add model 2023-10-18-asr_whisper_small_finnish_15k_samples_pipeline_fi * Add model 2023-10-18-asr_whisper_base_european_en * Add model 2023-10-18-asr_whisper_base_european_pipeline_en * Add model 2023-10-18-asr_whisper_small_vietnamese_tuananh7198_vi * Add model 2023-10-18-asr_whisper_small_vietnamese_tuananh7198_pipeline_vi * Add model 2023-10-18-asr_whisper_small_swedish_bm_pipeline_sv * Add model 2023-10-18-asr_whisper_tiny_european_en * Add model 2023-10-18-asr_whisper_tiny_european_pipeline_en * Add model 2023-10-18-asr_whisper_tiny_italian_1_it * Add model 2023-10-18-asr_whisper_tiny_italian_1_pipeline_it --------- Co-authored-by: ahmedlone127 * 2023-10-19-asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic_en (#14032) * Add model 2023-10-19-asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic_en * Add model 2023-10-19-asr_whisper_small_chinese_tw_voidful_en * Add model 2023-10-19-asr_whisper_small_chinese_tw_voidful_pipeline_en * Add model 2023-10-19-asr_whisper_small_bak_en * Add model 2023-10-19-asr_whisper_small_bak_pipeline_en * Add model 2023-10-19-asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic_en * Add model 2023-10-19-asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic_pipeline_en * Add model 2023-10-19-asr_personal_whisper_small_english_model_en * Add model 2023-10-19-asr_personal_whisper_small_english_model_pipeline_en * Add model 2023-10-19-asr_whisper_tiny_tamil_example_ta * Add model 2023-10-19-asr_whisper_tiny_tamil_example_pipeline_ta * Add model 2023-10-19-asr_whisper_small_hindi_xinhuang_pipeline_hi * Add model 2023-10-19-asr_whisper_small_swedish_test_3000_sv * Add model 2023-10-19-asr_whisper_small_hindi_xinhuang_hi * Add model 2023-10-19-asr_whisper_small_swedish_test_3000_pipeline_sv * Add model 2023-10-19-asr_whisper_malayalam_first_model_ml * Add model 2023-10-19-asr_whisper_malayalam_first_model_pipeline_ml * Add model 2023-10-19-asr_whisper_small_lithuanian_deividasm_lt * Add model 2023-10-19-asr_whisper_small_lithuanian_deividasm_pipeline_lt * Add model 2023-10-19-asr_whisper_lithuanian_finetune_lt * Add model 2023-10-19-asr_whisper_lithuanian_finetune_pipeline_lt * Add model 2023-10-19-asr_whisper_small_bengali_subhadeep_en * Add model 2023-10-19-asr_whisper_small_bengali_subhadeep_pipeline_en * Add model 2023-10-19-asr_whisper_small_chinesebasetw_zh * Add model 2023-10-19-asr_whisper_small_chinesebasetw_pipeline_zh * Add model 2023-10-19-asr_whisper_small_swedish_se_afroanton_en * Add model 2023-10-19-asr_whisper_small_swedish_se_afroanton_pipeline_en * Add model 2023-10-19-asr_whisper_small_uzbek_uz * Add model 2023-10-19-asr_whisper_small_uzbek_pipeline_uz * Add model 2023-10-19-asr_whisper_small_nepali_np_ne * Add model 2023-10-19-asr_whisper_small_nepali_np_pipeline_ne * Add model 2023-10-19-asr_whisper_small_polish_aspik101_pl * Add model 2023-10-19-asr_whisper_small_polish_aspik101_pipeline_pl * Add model 2023-10-19-asr_whisper_tiny_polish_pl * Add model 2023-10-19-asr_whisper_tiny_polish_pipeline_pl * Add model 2023-10-20-asr_whisper_small_english_blueraccoon_en * Add model 2023-10-20-asr_whisper_small_english_blueraccoon_pipeline_en * Add model 2023-10-20-asr_whisper_small_spanish_1e_6_en * Add model 2023-10-20-asr_whisper_small_dutch_nl * Add model 2023-10-20-asr_whisper_small_spanish_1e_6_pipeline_en * Add model 2023-10-20-asr_whisper_small_dutch_pipeline_nl * Add model 2023-10-20-asr_whisper_small_armenian_hy * Add model 2023-10-20-asr_whisper_small_armenian_pipeline_hy * Add model 2023-10-20-asr_whisper_small_finnish_sgangireddy_fi * Add model 2023-10-20-asr_whisper_small_finnish_sgangireddy_pipeline_fi * Add model 2023-10-20-asr_whisper_base_swedish_en * Add model 2023-10-20-asr_whisper_base_swedish_pipeline_en * Add model 2023-10-20-asr_whisper_small_lithuanian_serbian_v2_en * Add model 2023-10-20-asr_whisper_small_lithuanian_serbian_v2_pipeline_en * Add model 2023-10-20-asr_whisper_tiny_spanish_arpagon_es * Add model 2023-10-20-asr_whisper_tiny_spanish_arpagon_pipeline_es * Add model 2023-10-20-asr_whisper_small_french_yocel1_hi * Add model 2023-10-20-asr_whisper_small_french_yocel1_pipeline_hi * Add model 2023-10-20-asr_whisper_small_hungarian_cv11_en * Add model 2023-10-20-asr_whisper_small_hungarian_cv11_pipeline_en * Add model 2023-10-20-asr_whisper_small_swedish_torileatherman_sv * Add model 2023-10-20-asr_whisper_small_swedish_torileatherman_pipeline_sv * Add model 2023-10-20-asr_whisper_tiny_italian_local_en * Add model 2023-10-20-asr_whisper_tiny_italian_local_pipeline_en * Add model 2023-10-20-asr_whisper_small_arabic_cv11_en * Add model 2023-10-20-asr_whisper_small_arabic_cv11_pipeline_en * Add model 2023-10-20-asr_whisper_small_pashto_ihanif_ps * Add model 2023-10-20-asr_whisper_small_pashto_ihanif_pipeline_ps * Add model 2023-10-20-asr_whisper_small_swedish_english_se * Add model 2023-10-20-asr_whisper_small_swedish_english_pipeline_se * Add model 2023-10-20-asr_whisper_small_japanese_vumichien_ja * Add model 2023-10-20-asr_whisper_small_japanese_vumichien_pipeline_ja * Add model 2023-10-20-asr_whisper_small_mongolian_3_en * Add model 2023-10-20-asr_whisper_small_mongolian_3_pipeline_en * Add model 2023-10-20-asr_whisper_small_swe2_en * Add model 2023-10-20-asr_whisper_small_swe2_pipeline_en * Add model 2023-10-20-asr_whisper_tiny_italian_2_it * Add model 2023-10-20-asr_whisper_tiny_italian_2_pipeline_it * Add model 2023-10-20-asr_whisper_small_nob_no * Add model 2023-10-20-asr_whisper_small_nob_pipeline_no * Add model 2023-10-20-asr_whisper_danish_small_augmented_da * Add model 2023-10-20-asr_whisper_danish_small_augmented_pipeline_da * Add model 2023-10-20-asr_whisper_testrun1_en * Add model 2023-10-20-asr_whisper_testrun1_pipeline_en * Add model 2023-10-20-asr_whisper_small_korean_fl_ko * Add model 2023-10-20-asr_whisper_small_korean_fl_pipeline_ko * Add model 2023-10-20-asr_whisper_small_spanish_ari_pipeline_es * Add model 2023-10-20-asr_whisper_small_spanish_ari_es * Add model 2023-10-20-asr_whisper_small_punjabi_eastern_pa * Add model 2023-10-20-asr_whisper_small_punjabi_eastern_pipeline_pa --------- Co-authored-by: ahmedlone127 * 2023-10-24-bert_cn_finetuning_18811449050_en (#14039) * Add model 2023-10-25-fbert_aiclass_en * Add model 2023-10-25-bert_ft_qqp_1_jeevesh8_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_71_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_56_en * Add model 2023-10-25-bert_ft_qqp_2_jeevesh8_en * Add model 2023-10-25-xlm_bert_go_emotions_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_52_en * Add model 2023-10-25-bert_ft_qqp_3_jeevesh8_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_3_en * Add model 2023-10-25-cq_bert_model_repo_en * Add model 2023-10-25-bert_fine_trained_w_imdb_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_77_en * Add model 2023-10-25-bert_base_arabertv2_finetuned_emotion_3_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_48_en * Add model 2023-10-25-dkbert_hatespeech_detection_da * Add model 2023-10-25-bert_classifier_reddit_tc_en * Add model 2023-10-25-prot_bert_finetuned_localization_hazel0707_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_59_en * Add model 2023-10-25-bert_classifier_bert_base_uncased_hatexplain_rationale_two_en * Add model 2023-10-25-bert_regression_dynamic_tokenlimit_v1_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_66_en * Add model 2023-10-25-bert_multilingual_go_emtions_xx * Add model 2023-10-25-bert_ft_qqp_5_jeevesh8_en * Add model 2023-10-25-sikubert_finetuned_poetry_en * Add model 2023-10-25-bert_ft_qqp_7_jeevesh8_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_38_en * Add model 2023-10-25-fbert_ai_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_67_en * Add model 2023-10-25-bert_base_uncased_mnli_pietrolesci_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_64_en * Add model 2023-10-25-hatebert_ishate_29k_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_78_en * Add model 2023-10-25-bert_ft_qqp_11_jeevesh8_en * Add model 2023-10-25-bert_ft_qqp_0_jeevesh8_en * Add model 2023-10-25-bert_ft_qqp_4_jeevesh8_en * Add model 2023-10-25-bert_sequence_classifier_dehate_mono_english_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_21_en * Add model 2023-10-25-rubert_tweetsentiment_en * Add model 2023-10-25-bert_ft_qqp_13_jeevesh8_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_41_en * Add model 2023-10-25-indobertnews_en * Add model 2023-10-25-bert_ft_qqp_14_jeevesh8_en * Add model 2023-10-25-bert_sequence_classifier_dehate_mono_french_fr * Add model 2023-10-25-kobert_senti_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_14_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_1_en * Add model 2023-10-25-bert_asian_hate_tweets_self_unclean_en * Add model 2023-10-25-bert_ft_qqp_9_jeevesh8_en * Add model 2023-10-25-bert_classifier_biobert_v1.1_pub_section_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_23_en * Add model 2023-10-25-bert_ft_qqp_16_jeevesh8_en * Add model 2023-10-25-bert_ft_qqp_17_jeevesh8_en * Add model 2023-10-25-bert_base_banking77_pt2_laurie_en * Add model 2023-10-25-bert_for_pac_nl * Add model 2023-10-25-bert_sequence_classifier_dehate_mono_arabic_ar * Add model 2023-10-25-bert_ft_qqp_10_jeevesh8_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_79_en * Add model 2023-10-25-bert_ft_qqp_18_jeevesh8_en * Add model 2023-10-25-rubert_tiny_emotion_russian_cedr_m7_en * Add model 2023-10-25-autotrain_bert_nlp_3450894022_en * Add model 2023-10-25-bert_ft_qqp_19_jeevesh8_en * Add model 2023-10-25-bert_ft_qqp_12_jeevesh8_en * Add model 2023-10-25-bert_sequence_classifier_dehate_mono_italian_it * Add model 2023-10-25-bert_base_uncased_finetuned_glue_mrpc_en * Add model 2023-10-25-bert_ft_cola_1_en * Add model 2023-10-25-rubert_base_emotion_russian_cedr_m7_en * Add model 2023-10-25-bert_ft_qqp_21_jeevesh8_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_53_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_76_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_31_en * Add model 2023-10-25-bert_sequence_classifier_dehate_mono_polish_pl * Add model 2023-10-25-bert_base_cased_manifesto_2018_en * Add model 2023-10-25-bert_ft_qqp_23_jeevesh8_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_74_en * Add model 2023-10-25-bert_base_uncased_with_mrpc_trained_en * Add model 2023-10-25-tiny_bert_mnli_distilled_en * Add model 2023-10-25-bert_base_finetuned_emotion_en * Add model 2023-10-25-bert_italian_xxl_cased_itacola_en * Add model 2023-10-25-bert_ft_qqp_25_jeevesh8_en * Add model 2023-10-25-macedonian_bert_sentiment_classification_4labels_en * Add model 2023-10-25-bert_base_indonesian_522m_finetuned_sentiment_en * Add model 2023-10-25-bert_ft_qqp_26_jeevesh8_en * Add model 2023-10-25-bert_sequence_classifier_dehate_mono_spanish_es * Add model 2023-10-25-bert_base_uncased_stsb_jeremiahz_en * Add model 2023-10-25-bert_finetuned_banking77test_en * Add model 2023-10-25-bert_ft_qqp_27_jeevesh8_en * Add model 2023-10-25-bert_base_uncased_qnli_jeremiahz_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_73_en * Add model 2023-10-25-incivility_v1_final_tulio_chilean_spanish_bert_en * Add model 2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_clf_digimag_fa * Add model 2023-10-25-hate_v2_final_tulio_chilean_spanish_bert_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_25_en * Add model 2023-10-25-bert_base_uncased_mnli_jeremiahz_en * Add model 2023-10-25-bert_ft_qqp_29_jeevesh8_en * Add model 2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_binary_fa * Add model 2023-10-25-bert_ft_qqp_20_jeevesh8_en * Add model 2023-10-25-bert_base_uncased_qqp_jeremiahz_en * Add model 2023-10-25-tiny_bert_rte_distilled_en * Add model 2023-10-25-test_bert_training_en * Add model 2023-10-25-bert_base_uncased_wnli_jeremiahz_en * Add model 2023-10-25-bert_ft_qqp_15_jeevesh8_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_15_en * Add model 2023-10-25-deprem_bert_128k_v13_beta_tr * Add model 2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_clf_persiannews_fa * Add model 2023-10-25-std_0pnt2_bert_ft_cola_54_en * Add model 2023-10-25-bert_ft_qqp_30_jeevesh8_en * Add model 2023-10-25-subsimulator_bert_en * Add model 2023-10-25-tiny_bert_sst2_distilled_smith123_en * Add model 2023-10-25-bert_fine_tuned_cola_sanjay1234_en * Add model 2023-10-25-bert_classifier_bert_base_uncased_hatexplain_en * Add model 2023-10-25-indoberttypenews_en * Add model 2023-10-25-bert_classifier_rubertconv_toxic_clf_ru * Add model 2023-10-25-bert_base_uncased_sst_2_16_42_en * Add model 2023-10-25-bert_classifier_base_for_multilabel_sentence_classification_en * Add model 2023-10-25-finetune_bert_base_cased_en * Add model 2023-10-25-bert_ft_qqp_8_jeevesh8_en * Add model 2023-10-25-indobertnewstest_dimassamid_en * Add model 2023-10-25-bert_cn_finetuning_itcastai_en * Add model 2023-10-25-bert_base_finetuned_ynat_yooonsangbeom_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_10_en * Add model 2023-10-25-bert_cn_finetunning_itcastai_en * Add model 2023-10-25-scibert_finetuned_dagpap22_en * Add model 2023-10-25-bert_sequence_classifier_dehate_mono_german_de * Add model 2023-10-25-tiny_bert_wnli_distilled_en * Add model 2023-10-25-bert_ft_qqp_40_jeevesh8_en * Add model 2023-10-25-bert_asian_hate_tweets_self_unlean_with_clean_valid_en * Add model 2023-10-25-tiny_bert_qnli_distilled_en * Add model 2023-10-25-bert_ft_qqp_28_jeevesh8_en * Add model 2023-10-25-bert_base_uncased_sst_2_16_87_en * Add model 2023-10-25-bert_base_uncased_sst_2_32_42_en * Add model 2023-10-25-bert_base_uncased_sst_2_32_87_en * Add model 2023-10-25-bert_lf_en * Add model 2023-10-25-bert_base_finetuned_nli_jiwon_en * Add model 2023-10-25-bert_base_uncased_sst_2_32_100_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_61_en * Add model 2023-10-25-bert_ft_qqp_43_jeevesh8_en * Add model 2023-10-25-bert_base_uncased_sst_2_64_13_en * Add model 2023-10-25-bert_base_uncased_finetuned_claqua_cqi_en * Add model 2023-10-25-bert_ft_qqp_44_jeevesh8_en * Add model 2023-10-25-bert_base_uncased_finetuned_sufficiency_dagstuhl_otherseeds_en * Add model 2023-10-25-bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_9_en * Add model 2023-10-25-tiny_bert_sst2_distilled_youssef320_en * Add model 2023-10-25-bert_base_uncased_finetuned_claqua_cqa_predicate_en * Add model 2023-10-25-bert_ft_qqp_46_jeevesh8_en * Add model 2023-10-25-hate_v1_final_bert_base_spanish_wwm_cased_en * Add model 2023-10-25-bert_base_uncased_finetuned1_claqua_cqa_entity_en * Add model 2023-10-25-bert_lf_bond_en * Add model 2023-10-25-bert_ft_qqp_47_jeevesh8_en * Add model 2023-10-25-bert_large_uncased_sst_2_16_13_en * Add model 2023-10-25-bert_ft_qqp_48_jeevesh8_en * Add model 2023-10-25-bert_classifier_tiny_sst2_distilled_l4_h_512_en * Add model 2023-10-25-bert_base_uncased_finetuned_iemocap_en * Add model 2023-10-25-bert_ft_qqp_49_jeevesh8_en * Add model 2023-10-25-kobert_esg_en * Add model 2023-10-25-bert_base_uncased_stereoset_classifieronly_en * Add model 2023-10-25-bert_ft_qqp_50_jeevesh8_en * Add model 2023-10-25-bert_base_uncased_finetuned_iemocap_uptuna_en * Add model 2023-10-25-bert_ft_qqp_39_jeevesh8_en * Add model 2023-10-25-bert_ft_qqp_51_jeevesh8_en * Add model 2023-10-25-bioclinical_bert_ft_m3_lc_en * Add model 2023-10-25-burmese_bert_imdb_en * Add model 2023-10-25-mengzi_bert_base_fin_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1_zh * Add model 2023-10-25-goog_bert_ft_cola_4_en * Add model 2023-10-25-bert_classifier_german_sentiment_twitter_de * Add model 2023-10-25-bert_base_chinese_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1_zh * Add model 2023-10-25-bert_ft_qqp_53_jeevesh8_en * Add model 2023-10-25-goog_bert_ft_cola_2_en * Add model 2023-10-25-bert_fine_tuned_english_news_3_lbl_en * Add model 2023-10-25-deprem_bert_128k_tr * Add model 2023-10-25-bert_ft_qqp_54_jeevesh8_en * Add model 2023-10-25-bert_fine_tuned_english_news_2_lbl_en * Add model 2023-10-25-bert_large_uncased_sst_2_64_13_en * Add model 2023-10-25-bert_classifier_tiny_sst2_distilled_l6_h128_en * Add model 2023-10-25-goog_bert_ft_cola_5_en * Add model 2023-10-25-bert_base_uncased_finetuned_iemocap_uptuna3_en * Add model 2023-10-25-goog_bert_ft_cola_1_en * Add model 2023-10-25-bert_multilingual_sentiment_xx * Add model 2023-10-25-sqlclassification_normal_bert_model_en * Add model 2023-10-25-goog_bert_ft_cola_0_en * Add model 2023-10-25-bert_ft_qqp_58_jeevesh8_en * Add model 2023-10-25-codenlbert_tiny_en * Add model 2023-10-25-goog_bert_ft_cola_7_en * Add model 2023-10-25-bert_ft_qqp_34_jeevesh8_en * Add model 2023-10-25-goog_bert_ft_cola_6_en * Add model 2023-10-25-bert_ft_qqp_59_jeevesh8_en * Add model 2023-10-25-finetunedfinbert_model_en * Add model 2023-10-25-bert_ft_qqp_60_jeevesh8_en * Add model 2023-10-25-goog_bert_ft_cola_10_en * Add model 2023-10-25-bert_base_uncased_finetuned_iemocap5_en * Add model 2023-10-25-bert_ft_qqp_32_jeevesh8_en * Add model 2023-10-25-bert_ft_qqp_61_jeevesh8_en * Add model 2023-10-25-bert_ft_qqp_41_jeevesh8_en * Add model 2023-10-25-bert_ft_qqp_22_jeevesh8_en * Add model 2023-10-25-bert_base_uncased_finetuned_kaggle_predicting_effective_arguments_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_75_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_45_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_2_en * Add model 2023-10-25-codenlbert_samoan_en * Add model 2023-10-25-bert_fine_tuned_cola_huong_en * Add model 2023-10-25-bert_finetuned_imdb_wakaka_en * Add model 2023-10-25-knots_protbertbfd_alphafold_roa7n_en * Add model 2023-10-25-bert_large_uncased_sst_2_64_13_smoothed_en * Add model 2023-10-25-finetuned_sc_indobert_on_indonli_basic_train_en * Add model 2023-10-25-bert_ft_qqp_65_jeevesh8_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_43_en * Add model 2023-10-25-bert_base_uncased_finetuned_iemocap_uptuna5_en * Add model 2023-10-25-bert_ft_qqp_66_jeevesh8_en * Add model 2023-10-25-bert_base_uncased_sst_2_32_13_smoothed_en * Add model 2023-10-25-bert_base_uncased_finetuned_iemocap_uptuna6_en * Add model 2023-10-25-bert_ft_qqp_67_jeevesh8_en * Add model 2023-10-25-bert_base_uncased_sst_2_64_13_smoothed_en * Add model 2023-10-25-bert_base_uncased_finetuned_iemocap7_en * Add model 2023-10-25-goog_bert_ft_cola_17_en * Add model 2023-10-25-binary_fully_trained_bert_en * Add model 2023-10-25-bert_ft_qqp_57_jeevesh8_en * Add model 2023-10-25-bert_base_uncased_sst_2_16_13_smoothed_en * Add model 2023-10-25-bert_ft_qqp_69_jeevesh8_en * Add model 2023-10-25-goog_bert_ft_cola_16_en * Add model 2023-10-25-goog_bert_ft_cola_20_en * Add model 2023-10-25-bert_ft_qqp_70_jeevesh8_en * Add model 2023-10-25-bert_base_multilingual_cased_finetuned_review_xx * Add model 2023-10-25-bert_fine_tuned_cola_tamiti1610001_en * Add model 2023-10-25-bert_ft_qqp_71_jeevesh8_en * Add model 2023-10-25-goog_bert_ft_cola_13_en * Add model 2023-10-25-goog_bert_ft_cola_11_en * Add model 2023-10-25-deprem_bert_128k_v2_tr * Add model 2023-10-25-bert_base_uncased_finetuned_swift_v_shakes_en * Add model 2023-10-25-bert_large_uncased_sst_2_32_13_en * Add model 2023-10-25-goog_bert_ft_cola_8_en * Add model 2023-10-25-goog_bert_ft_cola_15_en * Add model 2023-10-25-bert_large_uncased_sst_2_32_13_smoothed_en * Add model 2023-10-25-covid_twitter_bert_v2_3_4_2e_05_0_01_en * Add model 2023-10-25-finbert_tsla_en * Add model 2023-10-25-backdoored_bert_finetuned_sst2_en * Add model 2023-10-25-bert_fine_tuned_cola_kaori1707_en * Add model 2023-10-25-bert_ft_qqp_74_jeevesh8_en * Add model 2023-10-25-esgbert_en * Add model 2023-10-25-bert_ft_qqp_63_jeevesh8_en * Add model 2023-10-25-bert_base_uncased_finetuned_iemocap8_en * Add model 2023-10-25-bert_base_uncased_sst_2_32_21_en * Add model 2023-10-25-bert_ft_qqp_76_jeevesh8_en * Add model 2023-10-25-goog_bert_ft_cola_27_en * Add model 2023-10-25-bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_14_en * Add model 2023-10-25-goog_bert_ft_cola_28_en * Add model 2023-10-25-bert_base_uncased_ituthesis2022mlvinikw_en * Add model 2023-10-25-bert_classifier_tiny_qqp_distilled_en * Add model 2023-10-25-bert_ft_qqp_37_jeevesh8_en * Add model 2023-10-25-goog_bert_ft_cola_25_en * Add model 2023-10-25-bert_ft_qqp_78_jeevesh8_en * Add model 2023-10-25-bert_base_finetuned_nli_jihyun22_en --------- Co-authored-by: ahmedlone127 * 2023-10-25-bert_ft_qqp_79_jeevesh8_en (#14040) * Add model 2023-10-25-bert_ft_qqp_68_jeevesh8_en * Add model 2023-10-25-bert_base_uncased_sst_2_32_13_30_en * Add model 2023-10-25-boss_sentiment_bert_base_uncased_en * Add model 2023-10-25-bert_mini_finetuned_sst2_en * Add model 2023-10-25-bert_ft_qqp_95_jeevesh8_en * Add model 2023-10-25-bert_tiny_finetuned_mnli_en * Add model 2023-10-25-bert_base_dutch_cased_finetuned_dt_en * Add model 2023-10-25-bert_tiny_finetuned_mrpc_en * Add model 2023-10-25-goog_bert_ft_cola_46_en * Add model 2023-10-25-bert_tiny_finetuned_qnli_en * Add model 2023-10-25-dk_emotion_bert_class_en * Add model 2023-10-25-goog_bert_ft_cola_47_en * Add model 2023-10-25-bert_tiny_finetuned_sst2_en * Add model 2023-10-25-dk_emotion_bert_2_en * Add model 2023-10-25-goog_bert_ft_cola_71_en * Add model 2023-10-25-bert_base_uncased_finetuned_iemocap_uptuna2_en * Add model 2023-10-25-goog_bert_ft_cola_73_en * Add model 2023-10-25-bert_classification_5ksamples_en * Add model 2023-10-25-bert_classifier_ara_multiclass_news_ar * Add model 2023-10-25-tonely_bert_en * Add model 2023-10-25-bert_base_uncased_sst_2_64_13_30_en * Add model 2023-10-25-bert_ft_cola_81_en * Add model 2023-10-25-bert_classification_10ksamples_en * Add model 2023-10-25-fine_tuned_indonli_augmented_with_indobert_large_p2_muhammadravi251001_en * Add model 2023-10-25-goog_bert_ft_cola_72_en * Add model 2023-10-25-bert_ft_cola_82_en * Add model 2023-10-25-bert_base_uncased_ag_news_finetuned_dwnews_categories_en * Add model 2023-10-25-rubert_large_emotion_russian_cedr_m7_en * Add model 2023-10-25-mengzi_bert_base_fin_ssec_en * Add model 2023-10-25-ogbv_gender_bert_hindi_english_hasoc20a_fin_en * Add model 2023-10-25-incivility_v2_final_tulio_chilean_spanish_bert_en * Add model 2023-10-25-bert_ft_cola_84_en * Add model 2023-10-25-goog_bert_ft_cola_63_en * Add model 2023-10-25-goog_bert_ft_cola_44_en * Add model 2023-10-25-goog_bert_ft_cola_14_en * Add model 2023-10-25-hindi_const21_hibert_final_en * Add model 2023-10-25-goog_bert_ft_cola_68_en * Add model 2023-10-25-goog_bert_ft_cola_69_en * Add model 2023-10-25-goog_bert_ft_cola_43_en * Add model 2023-10-25-bert_large_uncased_sst_2_16_13_30_en * Add model 2023-10-25-bert_classifier_bert_base_german_cased_gnad10_de * Add model 2023-10-25-bert_finetuned_mrpc_tiansiyuan_en * Add model 2023-10-25-bert_ft_cola_87_en * Add model 2023-10-25-goog_bert_ft_cola_52_en * Add model 2023-10-25-bert_tiny_finetuned_qqp_en * Add model 2023-10-25-goog_bert_ft_cola_53_en * Add model 2023-10-25-bert_base_uncased_sst_2_16_100_en * Add model 2023-10-25-bert_ft_cola_88_en * Add model 2023-10-25-goog_bert_ft_cola_39_en * Add model 2023-10-25-goog_bert_ft_cola_60_en * Add model 2023-10-25-bert_mixed_en * Add model 2023-10-25-bert_ft_qqp_83_jeevesh8_en * Add model 2023-10-25-bert_base_uncased_finetuned_question_v_statement_en * Add model 2023-10-25-bert_finetuning_test_milian_en * Add model 2023-10-25-baseline_bert_large_cased_epoch3_batch4_lr2e_05_w0_01_en * Add model 2023-10-25-goog_bert_ft_cola_36_en * Add model 2023-10-25-goog_bert_ft_cola_48_en * Add model 2023-10-25-bert_ft_qqp_97_jeevesh8_en * Add model 2023-10-25-bert_ft_qqp_35_jeevesh8_en * Add model 2023-10-25-goog_bert_ft_cola_19_en * Add model 2023-10-25-bert_finetunning_test_jovenpai_en * Add model 2023-10-25-bert_ft_cola_89_en * Add model 2023-10-25-bert_ft_cola_83_en * Add model 2023-10-25-goog_bert_ft_cola_75_en * Add model 2023-10-25-bert_sequence_classifier_base_uncased_sst2_en * Add model 2023-10-25-bert_large_uncased_sst_2_64_13_30_en * Add model 2023-10-25-tiny_bert_mrpc_distilled_en * Add model 2023-10-25-fine_tuned_indonli_translated_with_indobert_base_uncased_muhammadravi251001_en * Add model 2023-10-25-bert_ft_qqp_64_jeevesh8_en * Add model 2023-10-25-bert_ft_qqp_31_jeevesh8_en * Add model 2023-10-25-bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_sarahadnan_en * Add model 2023-10-25-goog_bert_ft_cola_56_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_16_en * Add model 2023-10-25-bert_mini_finetuned_mnli_en * Add model 2023-10-25-bert_base_uncased_mnli_sparse_70_unstructured_en * Add model 2023-10-25-bert_ft_cola_90_en * Add model 2023-10-25-finetuned_bert_mrpc_ndugar_en * Add model 2023-10-25-bert_ft_qqp_92_jeevesh8_en * Add model 2023-10-25-bert_ft_qqp_88_jeevesh8_en * Add model 2023-10-25-solved_finbert_tone_en * Add model 2023-10-25-deprem_berturk_binary_tr * Add model 2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_f1_v2_en * Add model 2023-10-25-bertabaporu_portuguese_irony_en * Add model 2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_sentiment_snappfood_fa * Add model 2023-10-25-goog_bert_ft_cola_51_en * Add model 2023-10-25-bert_base_uncased_sst_2_32_13_en * Add model 2023-10-25-fine_tuned_indonli_translated_with_indobert_large_p2_en * Add model 2023-10-25-goog_bert_ft_cola_37_en * Add model 2023-10-25-std_0pnt2_bert_ft_cola_62_en * Add model 2023-10-25-bert_ft_cola_91_en * Add model 2023-10-25-sentiment_hts2_hubert_hungarian_hu * Add model 2023-10-25-bert_ft_qqp_36_jeevesh8_en * Add model 2023-10-25-bert_wiki_comments_finetuned_en * Add model 2023-10-25-norsk_bert_fintuned_en * Add model 2023-10-25-bert_sim_pair_en * Add model 2023-10-25-bert_ft_qqp_62_jeevesh8_en * Add model 2023-10-25-bert_base_uncased_nisadibipolar_en * Add model 2023-10-25-samyarn_bert_base_multilingual_cased_xx * Add model 2023-10-25-bert_italian_sentiment_en * Add model 2023-10-25-bert_ft_cola_92_en * Add model 2023-10-25-fine_tuned_koreanindonli_kornli_with_bert_kor_base_en * Add model 2023-10-25-bert_mini_finetuned_qnli_en * Add model 2023-10-25-bert_ft_qqp_94_jeevesh8_en * Add model 2023-10-25-sentiment_hts5_hubert_hungarian_hu * Add model 2023-10-25-bert_ft_qqp_77_jeevesh8_en * Add model 2023-10-25-bert_ft_qqp_38_jeevesh8_en * Add model 2023-10-25-bert_tweets_semeval_unclean_en * Add model 2023-10-25-bert_ft_cola_80_en * Add model 2023-10-25-goog_bert_ft_cola_30_en * Add model 2023-10-25-bert_ft_qqp_75_jeevesh8_en * Add model 2023-10-25-fine_tuned_indonli_basic_with_indobert_base_uncased_afaji_en * Add model 2023-10-25-esg_bert_sector_classifier_en * Add model 2023-10-25-bert_mini_finetuned_stsb_en * Add model 2023-10-25-bert_large_uncased_sst_2_16_13_smoothed_en * Add model 2023-10-25-goog_bert_ft_cola_24_en * Add model 2023-10-25-bert_ft_cola_93_en * Add model 2023-10-25-bert_ft_qqp_90_jeevesh8_en * Add model 2023-10-25-bert_mini_finetuned_qqp_en * Add model 2023-10-25-goog_bert_ft_cola_33_en * Add model 2023-10-25-fine_tuned_indonli_augmented_with_indobert_large_p2_afaji_en * Add model 2023-10-25-bert_ft_cola_85_en * Add model 2023-10-25-bert_large_uncased_hoax_classifier_v1_en * Add model 2023-10-25-roberta_fake_real_en * Add model 2023-10-25-bert_tiny_finetuned_stsb_en * Add model 2023-10-25-bert_ft_qqp_86_jeevesh8_en * Add model 2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_multi_fa * Add model 2023-10-25-bert_base_uncased_reviews_4_en * Add model 2023-10-25-goog_bert_ft_cola_55_en * Add model 2023-10-25-fine_tuned_indonli_basic_with_indobert_large_p2_muhammadravi251001_en * Add model 2023-10-25-bert_ft_cola_94_en * Add model 2023-10-25-bert_large_uncased_sst_2_32_13_30_en * Add model 2023-10-25-bert_ft_qqp_42_jeevesh8_en * Add model 2023-10-25-bert_italian_irony_en * Add model 2023-10-25-bert_large_uncased_cola_b_en * Add model 2023-10-25-bert_ft_qqp_96_jeevesh8_en * Add model 2023-10-25-bert_base_mdoc_bm25_en * Add model 2023-10-25-bert_ft_cola_86_en * Add model 2023-10-25-bert_ft_qqp_84_jeevesh8_en * Add model 2023-10-25-goog_bert_ft_cola_9_en * Add model 2023-10-25-bert_base_multilingual_cased_mrpc_glue_xx * Add model 2023-10-25-goog_bert_ft_cola_54_en * Add model 2023-10-25-bert_finetuned_winogrande_en * Add model 2023-10-25-bert_fakenews_en * Add model 2023-10-25-bert_ft_cola_95_en * Add model 2023-10-25-goog_bert_ft_cola_57_en * Add model 2023-10-25-fine_tuned_indonli_augmented_with_indobert_base_uncased_muhammadravi251001_en * Add model 2023-10-25-bert_base_mdoc_hdct_en * Add model 2023-10-25-bert_ft_qqp_98_jeevesh8_en * Add model 2023-10-25-bert_sequce_classifier_paraphrase_en * Add model 2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_f1_v22_en * Add model 2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_sentiment_digikala_fa * Add model 2023-10-25-fine_tuned_indonli_basic_with_indobert_base_uncased_muhammadravi251001_en * Add model 2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_1_en * Add model 2023-10-25-goog_bert_ft_cola_40_en * Add model 2023-10-25-goog_bert_ft_cola_50_en * Add model 2023-10-25-goog_bert_ft_cola_12_en * Add model 2023-10-25-bert_base_uncased_finetuned_hateful_meme_en * Add model 2023-10-25-bert_ft_cola_96_en * Add model 2023-10-25-bert_ft_qqp_72_jeevesh8_en * Add model 2023-10-25-goog_bert_ft_cola_22_en * Add model 2023-10-25-bert_wikipedia_sst2_en * Add model 2023-10-25-goog_bert_ft_cola_26_en * Add model 2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_2_en * Add model 2023-10-25-bert_deepfake_bulgarian_multiclass_bg * Add model 2023-10-25-bert_ft_qqp_52_jeevesh8_en * Add model 2023-10-25-bert_ft_qqp_56_jeevesh8_en * Add model 2023-10-25-goog_bert_ft_cola_49_en * Add model 2023-10-25-goog_bert_ft_cola_64_en * Add model 2023-10-25-indobertnewstest_rizalmilyardi_en * Add model 2023-10-25-a01_suicide_bert_huggingface_finetune_en * Add model 2023-10-25-bert_base_arabic_camelbert_msa_finetuned_arabic_dialect_identification_model_1_ar * Add model 2023-10-25-bert_base_uncased_sst_2_16_13_30_en * Add model 2023-10-25-bert_ft_cola_97_en * Add model 2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_3_en * Add model 2023-10-25-bert_ft_qqp_45_jeevesh8_en * Add model 2023-10-25-goog_bert_ft_cola_32_en * Add model 2023-10-25-goog_bert_ft_cola_74_en * Add model 2023-10-25-norbert2_sentiment_norec_2_en * Add model 2023-10-25-biobert_finetuned_genetic_mutation_en * Add model 2023-10-25-bert_sequence_classifier_paraphrase_pt * Add model 2023-10-25-bert_sim_doc_en * Add model 2023-10-25-goog_bert_ft_cola_70_en * Add model 2023-10-25-goog_bert_ft_cola_42_en * Add model 2023-10-25-bert_finetuning_test_itcastai_en * Add model 2023-10-25-bert_ft_cola_98_en * Add model 2023-10-25-goog_bert_ft_cola_18_en * Add model 2023-10-25-baseline_bert_base_cased_epoch3_batch4_lr2e_05_w0_01_en * Add model 2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_4_en * Add model 2023-10-25-bert_ft_qqp_99_jeevesh8_en * Add model 2023-10-25-bert_classifier_dehate_mono_indonesian_en * Add model 2023-10-25-bert_italian_hate_speech_en * Add model 2023-10-25-bert_classifier_base_uncased_qnli_en * Add model 2023-10-25-goog_bert_ft_cola_21_en * Add model 2023-10-25-goog_bert_ft_cola_31_en * Add model 2023-10-25-goog_bert_ft_cola_67_en * Add model 2023-10-25-a02_suicide_bert_huggingface_finetune_en * Add model 2023-10-25-bert_classifier_finbert_en * Add model 2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_5_en * Add model 2023-10-25-bert_ft_cola_99_en * Add model 2023-10-25-bert_ft_qqp_82_jeevesh8_en * Add model 2023-10-25-goog_bert_ft_cola_3_en * Add model 2023-10-25-bert_base_chinese_finetuned_binary_best_en * Add model 2023-10-25-bert_classification_1500samples_en * Add model 2023-10-25-goog_bert_ft_cola_35_en * Add model 2023-10-25-tiny_bert_sst2_distilled_kushaljoseph_en * Add model 2023-10-25-goog_bert_ft_cola_65_en * Add model 2023-10-25-chinese_roberta_wwm_ext_finetuned_binary_en * Add model 2023-10-25-goog_bert_ft_cola_58_en * Add model 2023-10-25-norbert2_sentiment_norec_4_en * Add model 2023-10-25-bert_classifier_russian_base_srl_ru * Add model 2023-10-25-goog_bert_ft_cola_59_en * Add model 2023-10-25-covid_twitter_bert_v2_mnli_nli_sts_crossencoder_covid_hera_en * Add model 2023-10-25-norbert2_sentiment_norec_6_en * Add model 2023-10-25-legal_bert_tpb_clause_class_en * Add model 2023-10-25-goog_bert_ft_cola_61_en * Add model 2023-10-25-twitter_disaster_bert_large_en * Add model 2023-10-25-goog_bert_ft_cola_62_en * Add model 2023-10-25-bert_large_uncased_mnli_ofirzaf_en * Add model 2023-10-25-norbert2_sentiment_norec_7_en * Add model 2023-10-25-bert_classifier_riad_finetuned_mrpc_en * Add model 2023-10-25-bert_base_cased_finetuned_cola_sreyang_nvidia_en * Add model 2023-10-25-bert_base_uncased_research_articles_multilabel_en * Add model 2023-10-25-goog_bert_ft_cola_66_en * Add model 2023-10-25-mini_bert_distilled_en * Add model 2023-10-25-bert_fom_job_description_assignment_en * Add model 2023-10-25-goog_bert_ft_cola_76_en * Add model 2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_6_en * Add model 2023-10-25-finbert_finetuned_fg_single_sentence_news_weighted_en * Add model 2023-10-25-bert_cl_cf_1700_en * Add model 2023-10-25-goog_bert_ft_cola_77_en * Add model 2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_7_en * Add model 2023-10-25-bert_classifier_prot_bfd_localization_en * Add model 2023-10-25-bert_cl_g_1700_en * Add model 2023-10-25-bert_sentence_classifier_en * Add model 2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_8_en * Add model 2023-10-25-goog_bert_ft_cola_81_en * Add model 2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_9_en * Add model 2023-10-25-rubert_rusentitweet_sismetanin_en * Add model 2023-10-25-goog_bert_ft_cola_91_en * Add model 2023-10-25-norbert2_sentiment_norec_8_en * Add model 2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_10_en * Add model 2023-10-25-goog_bert_ft_cola_89_en * Add model 2023-10-25-bert_base_uncased_random_weights_s42_en * Add model 2023-10-25-norbert2_sentiment_norec_9_en * Add model 2023-10-25-bert_base_uncased_finetuned_cola_ruizhou_en * Add model 2023-10-25-fine_tuned_koreanindonli_kornli_with_bert_base_en * Add model 2023-10-25-goog_bert_ft_cola_82_en * Add model 2023-10-25-finbert_fls_en * Add model 2023-10-25-bert_base_uncased_finetuned_mrpc_ruizhou_en * Add model 2023-10-25-bert_cnn_news_en --------- Co-authored-by: ahmedlone127 * 2023-10-25-bert_classifier_finbert_esg_en (#14041) * Add model 2023-10-25-bert_classifier_finbert_esg_en * Add model 2023-10-25-imdb_bert_base_uncased_kyle1668_en * Add model 2023-10-25-bert_base_uncased_finetuned_rte_ruizhou_en * Add model 2023-10-25-goog_bert_ft_cola_88_en * Add model 2023-10-25-emobert_single_binary_en * Add model 2023-10-25-bert_base_uncased_hate_offensive_oriya_normal_speech_en * Add model 2023-10-25-bert_base_arabertv2_jehadoumer_en * Add model 2023-10-25-22_languages_bert_base_cased_en * Add model 2023-10-25-goog_bert_ft_cola_87_en * Add model 2023-10-25-bert_base_chinese_finetuned_mosei_en * Add model 2023-10-25-bert_finetuned_winogrande83e_058_en * Add model 2023-10-25-bert_base_arabertv22a_preprocessed_en * Add model 2023-10-25-goog_bert_ft_cola_86_en * Add model 2023-10-25-rubert_base_corruption_detector_ru * Add model 2023-10-25-gbert_base_ft_edu_redux_de * Add model 2023-10-25-goog_bert_ft_cola_92_en * Add model 2023-10-25-bert_base_arabertv2_nouman_10_en * Add model 2023-10-25-bert_base_chinese_finetuned_mosei1_en * Add model 2023-10-25-bert_classifier_distil_base_uncased_finetuned_emotion_en * Add model 2023-10-25-sena_finetuned_bert_en * Add model 2023-10-25-goog_bert_ft_cola_93_en * Add model 2023-10-25-bert_classifier_hashtag_tonga_tonga_islands_hashtag_20_en * Add model 2023-10-25-bert_base_cased_fake_real_en * Add model 2023-10-25-bangla_fake_news_mbert_en * Add model 2023-10-25-bert_base_banking77_pt2_shahzay_en * Add model 2023-10-25-goog_bert_ft_cola_84_en * Add model 2023-10-25-gbert_large_ft_edu_redux_de * Add model 2023-10-25-rubert_base_cased_sentiment_nepal_bhasa_ru * Add model 2023-10-25-goog_bert_ft_cola_83_en * Add model 2023-10-25-bert_base_cased_fake_real_2_en * Add model 2023-10-25-bert_base_arabertv02_twitter_en * Add model 2023-10-25-emobert_valence_5_en * Add model 2023-10-25-bert_base_cased_fake_real_3_en * Add model 2023-10-25-bert_base_cased_mnli_tehrannlp_en * Add model 2023-10-25-goog_bert_ft_cola_85_en * Add model 2023-10-25-bert_base_arabertv2test_en * Add model 2023-10-25-6ep_bert_ft_cola_0_en * Add model 2023-10-25-goog_bert_ft_cola_79_en * Add model 2023-10-25-bert_base_uncased_mnli_tehrannlp_en * Add model 2023-10-25-6ep_bert_ft_cola_1_en * Add model 2023-10-25-bert_base_uncased_hoax_classifier_fulltext_v1_en * Add model 2023-10-25-goog_bert_ft_cola_78_en * Add model 2023-10-25-rubert_sentence_mixin_en * Add model 2023-10-25-bert_base_cased_avg_cola_en * Add model 2023-10-25-6ep_bert_ft_cola_2_en * Add model 2023-10-25-finbert_narsil_en * Add model 2023-10-25-goog_bert_ft_cola_80_en * Add model 2023-10-25-6ep_bert_ft_cola_3_en * Add model 2023-10-25-bert_base_cased_avg_mnli_en * Add model 2023-10-25-goog_bert_ft_cola_99_en * Add model 2023-10-25-bert_base_uncased_avg_cola_2e_5_21_en * Add model 2023-10-25-6ep_bert_ft_cola_4_en * Add model 2023-10-25-bert_base_cased_resume_classification_en * Add model 2023-10-25-bert_large_uncased_crows_pairs_classifieronly_en * Add model 2023-10-25-goog_bert_ft_cola_95_en * Add model 2023-10-25-bert_base_uncased_avg_cola_2e_5_42_en * Add model 2023-10-25-6ep_bert_ft_cola_5_en * Add model 2023-10-25-bert_large_uncased_crows_pairs_finetuned_en * Add model 2023-10-25-kcbert_en * Add model 2023-10-25-goog_bert_ft_cola_96_en * Add model 2023-10-25-bert_base_uncased_avg_cola_2e_5_63_en * Add model 2023-10-25-6ep_bert_ft_cola_6_en * Add model 2023-10-25-goog_bert_ft_cola_98_en * Add model 2023-10-25-bert_multilingual_xx * Add model 2023-10-25-6ep_bert_ft_cola_7_en * Add model 2023-10-25-bert_large_uncased_stereoset_classifieronly_en * Add model 2023-10-25-bert_base_uncased_avg_mnli_2e_5_21_en * Add model 2023-10-25-goog_bert_ft_cola_97_en * Add model 2023-10-25-bert_base_uncased_finetuned_binary_classification_en * Add model 2023-10-25-bert_base_uncased_avg_mnli_2e_5_63_en * Add model 2023-10-25-6ep_bert_ft_cola_8_en * Add model 2023-10-25-bert_large_uncased_winobias_finetuned_en * Add model 2023-10-25-goog_bert_ft_cola_94_en * Add model 2023-10-25-bert_base_uncased_avg_mnli_en * Add model 2023-10-25-6ep_bert_ft_cola_9_en * Add model 2023-10-25-bertimbau_hate_speech_en * Add model 2023-10-25-goog_bert_ft_cola_29_en * Add model 2023-10-25-bert_base_uncased_avg_sst2_2e_5_21_en * Add model 2023-10-25-6ep_bert_ft_cola_10_en * Add model 2023-10-25-bert_large_uncased_winobias_classifieronly_en * Add model 2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v1_en * Add model 2023-10-25-6ep_bert_ft_cola_11_en * Add model 2023-10-25-bert_base_uncased_avg_sst2_2e_5_42_en * Add model 2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v2_en * Add model 2023-10-25-bert_classifier_shahma_finetuned_mrpc_en * Add model 2023-10-25-bert_base_uncased_finetuned_winogrande_debiased_en * Add model 2023-10-25-bert_base_chinese_ssec_en * Add model 2023-10-25-6ep_bert_ft_cola_12_en * Add model 2023-10-25-bert_base_uncased_ft_m3_lc_en * Add model 2023-10-25-german_tweetstance_bert_uncased_russiaukrainewar_de * Add model 2023-10-25-bert_base_uncased_avg_sst2_2e_5_63_en * Add model 2023-10-25-bert_tiny_goodreads_wandb_en * Add model 2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v4_en * Add model 2023-10-25-bert_base_uncase_contracts_en * Add model 2023-10-25-6ep_bert_ft_cola_13_en * Add model 2023-10-25-bert_base_uncased_cls_hatexplain_en * Add model 2023-10-25-bert_base_uncased_finetuned_wnli_sumaia_en * Add model 2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v5_en * Add model 2023-10-25-6ep_bert_ft_cola_14_en * Add model 2023-10-25-bert_base_uncased_cls_mnli_en * Add model 2023-10-25-legal_bert_based_uncase_en * Add model 2023-10-25-tyson_bert_base_cased_en * Add model 2023-10-25-tiny_bert_mnli_m_distilled_en * Add model 2023-10-25-bert_finetuned_mrpc_trainerclass_en * Add model 2023-10-25-bert_base_uncased_cls_sst2_en * Add model 2023-10-25-6ep_bert_ft_cola_15_en * Add model 2023-10-25-tiny_bert_sst2_distilled_l4_h_512_new_en * Add model 2023-10-25-bert_claimcoherence_mini_en * Add model 2023-10-25-6ep_bert_ft_cola_16_en * Add model 2023-10-25-bert_base_uncased_mrpc_2e_5_42_en * Add model 2023-10-25-scibert_scivocab_uncased_ft_m3_lc_en * Add model 2023-10-25-tweet_bert_1408_en * Add model 2023-10-25-autotrain_test_4_macbert_1071837613_en * Add model 2023-10-25-bert_base_uncased_qqp_2e_5_42_en * Add model 2023-10-25-6ep_bert_ft_cola_17_en * Add model 2023-10-25-bert_finetuned_char_classification_en * Add model 2023-10-25-norbert2_sentiment_norec_12_en * Add model 2023-10-25-bert_base_cased_twitter_sentiment_en * Add model 2023-10-25-6ep_bert_ft_cola_18_en * Add model 2023-10-25-bert_classifier_base_styleclassification_subjective_neutral_en * Add model 2023-10-25-model3_marabertv2_t1_en * Add model 2023-10-25-bert_base_uncased_emotion_damamsaketh19_en * Add model 2023-10-25-tiny_bert_mnli_mm_distilled_en * Add model 2023-10-25-ziwei_bert_imdb_en * Add model 2023-10-25-6ep_bert_ft_cola_19_en * Add model 2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_1_en * Add model 2023-10-25-tiny_bert_stsb_distilled_en * Add model 2023-10-25-finetuned_bert_yelp_v1_en * Add model 2023-10-25-6ep_bert_ft_cola_20_en * Add model 2023-10-25-ziwei_bertimdb_prob_en * Add model 2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_2_en * Add model 2023-10-25-rubert_base_cased_conversational_paraphrase_v1_ru * Add model 2023-10-25-esgbert1_en * Add model 2023-10-25-tiny_bert_sst2_distilled_kaitlineryan99_en * Add model 2023-10-25-6ep_bert_ft_cola_21_en * Add model 2023-10-25-finetuned_iitp_pdt_review_additionalpretrained_bert_base_cased_en * Add model 2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_3_en * Add model 2023-10-25-finetuned_iitp_pdt_review_bert_hinglish_big_en * Add model 2023-10-25-norbert2_sentiment_norec_13_en * Add model 2023-10-25-mascorpus_bert_classifier_en * Add model 2023-10-25-6ep_bert_ft_cola_22_en * Add model 2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_4_en * Add model 2023-10-25-finetuned_iitp_pdt_review_bert_hinglish_small_en * Add model 2023-10-25-6ep_bert_ft_cola_23_en * Add model 2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_5_en * Add model 2023-10-25-bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_polifact_en * Add model 2023-10-25-finetuned_iitpmovie_additionalpretrained_bert_base_cased_en * Add model 2023-10-25-norbert2_sentiment_norec_14_en * Add model 2023-10-25-6ep_bert_ft_cola_24_en * Add model 2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_6_en * Add model 2023-10-25-tiny_bert_qqp_128_distilled_en * Add model 2023-10-25-finetuned_sail2017_additionalpretrained_bert_base_cased_en * Add model 2023-10-25-6ep_bert_ft_cola_25_en * Add model 2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_7_en * Add model 2023-10-25-bluebert_sitesentence_diagnosis_classification_en * Add model 2023-10-25-norbert2_sentiment_norec_16_en * Add model 2023-10-25-finetuned_sail2017_bert_base_cased_en * Add model 2023-10-25-6ep_bert_ft_cola_26_en * Add model 2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_8_en * Add model 2023-10-25-fine_tune_bert_exist_en * Add model 2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_9_en * Add model 2023-10-25-6ep_bert_ft_cola_27_en * Add model 2023-10-25-klue_bert_base_re_ainize_en * Add model 2023-10-25-norbert2_sentiment_norec_tonga_tonga_islands_gpu_3000_rader_en * Add model 2023-10-25-6ep_bert_ft_cola_28_en * Add model 2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_10_en * Add model 2023-10-25-gbert_base_germeval21_toxic_with_data_augmentation_en * Add model 2023-10-25-6ep_bert_ft_cola_29_en * Add model 2023-10-25-fine_tune_mbert_exist_en * Add model 2023-10-25-bow_bert_en * Add model 2023-10-25-gbert_base_germeval21_toxic_en * Add model 2023-10-25-bert_finetuned_char_classification_e15_en * Add model 2023-10-25-6ep_bert_ft_cola_30_en * Add model 2023-10-25-bert_base_uncased_finetuned_osdg_en * Add model 2023-10-25-fine_tune_bert_combined_en * Add model 2023-10-25-bert_base_uncased_finetuned_cola_ajrae_en * Add model 2023-10-26-model3_marabertv2_t1_wos_en * Add model 2023-10-26-6ep_bert_ft_cola_31_en * Add model 2023-10-26-bert_base_nli_mean_tokens_finetuned_polifact_en * Add model 2023-10-26-bert_base_uncased_finetuned_mrpc_ajrae_en * Add model 2023-10-26-model3_marabertv2_t2_wos_en * Add model 2023-10-26-tiny_bert_sst2_distilled_linxi_en * Add model 2023-10-26-finbert_pb_en * Add model 2023-10-26-6ep_bert_ft_cola_32_en * Add model 2023-10-26-bert_turkish_text_classification_tr * Add model 2023-10-26-thext_ai_scibert_en * Add model 2023-10-26-model5_arabertv2_large_t1_wos_en * Add model 2023-10-26-fine_tune_mbert_combined_en * Add model 2023-10-26-6ep_bert_ft_cola_33_en * Add model 2023-10-26-bert_eatable_classification_english_russian_en * Add model 2023-10-26-dk_emotion_bert_in_class_ejaalborg2022_en * Add model 2023-10-26-thext_bio_scibert_en * Add model 2023-10-26-6ep_bert_ft_cola_34_en * Add model 2023-10-26-bert_base_uncased_itr0_0_0001_all_01_03_2022_14_08_15_en * Add model 2023-10-26-bert_large_uncased_hoax_classifier_fulltext_v1_en * Add model 2023-10-26-6ep_bert_ft_cola_35_en * Add model 2023-10-26-thext_czech_scibert_en * Add model 2023-10-26-bert_base_uncased_itr0_0_0001_webdiscourse_01_03_2022_16_08_12_en * Add model 2023-10-26-model4_arabertv2_base_t1_ws_a100_en * Add model 2023-10-26-validate_bert_base_en * Add model 2023-10-26-6ep_bert_ft_cola_36_en * Add model 2023-10-26-bert_base_mnli_en * Add model 2023-10-26-bert_classifier_2e16_en * Add model 2023-10-26-model3_marabertv2_t1_ws_a100_en * Add model 2023-10-26-6ep_bert_ft_cola_37_en * Add model 2023-10-26-autonlp_alberti_stanza_names_34318169_en * Add model 2023-10-26-model4_arabertv2_base_t2_ws_a100_en * Add model 2023-10-26-6ep_bert_ft_cola_38_en * Add model 2023-10-26-validate_bert_large_en * Add model 2023-10-26-bert_multilingual_passage_reranking_msmarco_amberoad_xx * Add model 2023-10-26-6ep_bert_ft_cola_39_en * Add model 2023-10-26-model3_marabertv2_t2_ws_a100_en * Add model 2023-10-26-bert_large_uncased_fine_tune_winogrande_ep_8_en * Add model 2023-10-26-bert_finetuned_char_classification_e8_en * Add model 2023-10-26-bert_base_uncased_finetuned_cola_anirudh21_en * Add model 2023-10-26-6ep_bert_ft_cola_40_en * Add model 2023-10-26-bert_large_uncased_finetuned_winogrande_en * Add model 2023-10-26-bert_vast_binary_en * Add model 2023-10-26-6ep_bert_ft_cola_41_en * Add model 2023-10-26-bert_base_uncased_finetuned_mrpc_anirudh21_en * Add model 2023-10-26-finbert_slow_en * Add model 2023-10-26-bert_finetuned_char_classification_e81_en * Add model 2023-10-26-bert_base_uncased_finetuned_qnli_anirudh21_en * Add model 2023-10-26-6ep_bert_ft_cola_42_en * Add model 2023-10-26-bert_classifier_base_cased_chuvash_studio_name_medium_en * Add model 2023-10-26-kd_roberta_1lbert_lambda50_en * Add model 2023-10-26-tiny_bert_qnli_128_distilled_en * Add model 2023-10-26-bert_base_uncased_finetuned_rte_anirudh21_en * Add model 2023-10-26-6ep_bert_ft_cola_43_en * Add model 2023-10-26-tiny_bert_cola_128_distilled_en * Add model 2023-10-26-bert_large_uncased_fine_tune_winogrande_ep_8_original_2e_en * Add model 2023-10-26-tiny_bert_qnli128_distilled_en * Add model 2023-10-26-bert_base_uncased_finetuned_wnli_anirudh21_en * Add model 2023-10-26-6ep_bert_ft_cola_44_en * Add model 2023-10-26-bert_base_uncased_fine_tune_winogrande_ep_8_original_2e_en * Add model 2023-10-26-bert_workforce_en * Add model 2023-10-26-bert_base_uncased_finetuned_addresso_en * Add model 2023-10-26-6ep_bert_ft_cola_45_en * Add model 2023-10-26-tinybertje_v2_en * Add model 2023-10-26-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v1_en * Add model 2023-10-26-bert_base_uncased_finetuned_coda19_en * Add model 2023-10-26-6ep_bert_ft_cola_46_en * Add model 2023-10-26-filbert_en * Add model 2023-10-26-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v2_en * Add model 2023-10-26-scibert_uncased_finetuned_coda19_en * Add model 2023-10-26-6ep_bert_ft_cola_47_en * Add model 2023-10-26-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v3_en * Add model 2023-10-26-6ep_bert_ft_cola_48_en * Add model 2023-10-26-bert_base_emotion_en --------- Co-authored-by: ahmedlone127 --------- Co-authored-by: jsl-models <74001263+jsl-models@users.noreply.github.com> Co-authored-by: ahmedlone127 Co-authored-by: prabod Co-authored-by: DevinTDHa Co-authored-by: Devin Ha <33089471+DevinTDHa@users.noreply.github.com> Co-authored-by: LIN-Yu-Ting Co-authored-by: SKocer --- ...gle_Job_data_tuned_trial_2_11_2_2022_en.md | 93 +++++++++++++++ ...3-10-17-asr_whisper_base_bulgarian_l_en.md | 92 ++++++++++++++ ...sr_whisper_base_bulgarian_l_pipeline_en.md | 71 +++++++++++ .../2023-10-17-asr_whisper_base_english_en.md | 92 ++++++++++++++ ...17-asr_whisper_base_english_pipeline_en.md | 71 +++++++++++ ...2023-10-17-asr_whisper_base_pipeline_xx.md | 71 +++++++++++ .../2023-10-17-asr_whisper_base_xx.md | 92 ++++++++++++++ .../2023-10-17-asr_whisper_kannada_base_kn.md | 92 ++++++++++++++ ...17-asr_whisper_kannada_base_pipeline_kn.md | 71 +++++++++++ ...2023-10-17-asr_whisper_kannada_small_kn.md | 92 ++++++++++++++ ...7-asr_whisper_kannada_small_pipeline_kn.md | 71 +++++++++++ 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docs/_posts/ahmedlone127/2023-10-26-tiny_bert_sst2_distilled_linxi_en.md create mode 100644 docs/_posts/ahmedlone127/2023-10-26-tinybertje_v2_en.md create mode 100644 docs/_posts/ahmedlone127/2023-10-26-validate_bert_base_en.md create mode 100644 docs/_posts/ahmedlone127/2023-10-26-validate_bert_large_en.md diff --git a/docs/_posts/ahmedlone127/2023-09-15-google_Job_data_tuned_trial_2_11_2_2022_en.md b/docs/_posts/ahmedlone127/2023-09-15-google_Job_data_tuned_trial_2_11_2_2022_en.md new file mode 100644 index 00000000000000..53f8d0bd36e848 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-09-15-google_Job_data_tuned_trial_2_11_2_2022_en.md @@ -0,0 +1,93 @@ +--- +layout: model +title: English google_Job_data_tuned_trial_2_11_2_2022 DistilBertEmbeddings from EslamAhmed +author: John Snow Labs +name: google_Job_data_tuned_trial_2_11_2_2022 +date: 2023-09-15 +tags: [distilbert, en, open_source, fill_mask, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.2 +spark_version: 3.0 +supported: true +engine: onnx +annotator: DistilBertEmbeddings +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained DistilBertEmbeddings model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`google_Job_data_tuned_trial_2_11_2_2022` is a English model originally trained by EslamAhmed. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/google_Job_data_tuned_trial_2_11_2_2022_en_5.1.2_3.0_1694736099439.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/google_Job_data_tuned_trial_2_11_2_2022_en_5.1.2_3.0_1694736099439.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + + +document_assembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("documents") + + +embeddings =DistilBertEmbeddings.pretrained("google_Job_data_tuned_trial_2_11_2_2022","en") \ + .setInputCols(["documents","token"]) \ + .setOutputCol("embeddings") + +pipeline = Pipeline().setStages([document_assembler, embeddings]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("embeddings") + +val embeddings = DistilBertEmbeddings + .pretrained("google_Job_data_tuned_trial_2_11_2_2022", "en") + .setInputCols(Array("documents","token")) + .setOutputCol("embeddings") + +val pipeline = new Pipeline().setStages(Array(document_assembler, embeddings)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|google_Job_data_tuned_trial_2_11_2_2022| +|Compatibility:|Spark NLP 5.1.2+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[embeddings]| +|Language:|en| +|Size:|402.3 MB| + +## References + +https://huggingface.co/EslamAhmed/google_Job_data_tuned_trial_2_11-2-2022 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_base_bulgarian_l_en.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_base_bulgarian_l_en.md new file mode 100644 index 00000000000000..5b2602e6c9e594 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_base_bulgarian_l_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_base_bulgarian_l WhisperForCTC from nandovallec +author: John Snow Labs +name: asr_whisper_base_bulgarian_l +date: 2023-10-17 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_base_bulgarian_l` is a English model originally trained by nandovallec. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_base_bulgarian_l_en_5.1.4_3.4_1697581811339.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_base_bulgarian_l_en_5.1.4_3.4_1697581811339.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_base_bulgarian_l","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_base_bulgarian_l","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_base_bulgarian_l| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|643.5 MB| + +## References + +https://huggingface.co/nandovallec/whisper-base-bg-l \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_base_bulgarian_l_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_base_bulgarian_l_pipeline_en.md new file mode 100644 index 00000000000000..8a864efc477d67 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_base_bulgarian_l_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_base_bulgarian_l_pipeline pipeline WhisperForCTC from nandovallec +author: John Snow Labs +name: asr_whisper_base_bulgarian_l_pipeline +date: 2023-10-17 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_base_bulgarian_l_pipeline` is a English model originally trained by nandovallec. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_base_bulgarian_l_pipeline_en_5.1.4_3.4_1697581823071.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_base_bulgarian_l_pipeline_en_5.1.4_3.4_1697581823071.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_base_bulgarian_l_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_base_bulgarian_l_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_base_bulgarian_l_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|643.5 MB| + +## References + +https://huggingface.co/nandovallec/whisper-base-bg-l + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_base_english_en.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_base_english_en.md new file mode 100644 index 00000000000000..68b1876ecf1a57 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_base_english_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_base_english WhisperForCTC from openai +author: John Snow Labs +name: asr_whisper_base_english +date: 2023-10-17 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_base_english` is a English model originally trained by openai. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_base_english_en_5.1.4_3.4_1697584638867.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_base_english_en_5.1.4_3.4_1697584638867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_base_english","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_base_english","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_base_english| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|406.2 MB| + +## References + +https://huggingface.co/openai/whisper-base.en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_base_english_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_base_english_pipeline_en.md new file mode 100644 index 00000000000000..85e727d52d6f80 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_base_english_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_base_english_pipeline pipeline WhisperForCTC from openai +author: John Snow Labs +name: asr_whisper_base_english_pipeline +date: 2023-10-17 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_base_english_pipeline` is a English model originally trained by openai. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_base_english_pipeline_en_5.1.4_3.4_1697584648732.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_base_english_pipeline_en_5.1.4_3.4_1697584648732.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_base_english_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_base_english_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_base_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|406.2 MB| + +## References + +https://huggingface.co/openai/whisper-base.en + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_base_pipeline_xx.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_base_pipeline_xx.md new file mode 100644 index 00000000000000..7d468b167dc31d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_base_pipeline_xx.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Multilingual asr_whisper_base_pipeline pipeline WhisperForCTC from openai +author: John Snow Labs +name: asr_whisper_base_pipeline +date: 2023-10-17 +tags: [whisper, xx, open_source, pipeline] +task: Automatic Speech Recognition +language: xx +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_base_pipeline` is a Multilingual model originally trained by openai. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_base_pipeline_xx_5.1.4_3.4_1697580478931.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_base_pipeline_xx_5.1.4_3.4_1697580478931.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_base_pipeline', lang = 'xx') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_base_pipeline', lang = 'xx') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|398.5 MB| + +## References + +https://huggingface.co/openai/whisper-base + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_base_xx.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_base_xx.md new file mode 100644 index 00000000000000..2b86bf69a190f7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_base_xx.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Multilingual asr_whisper_base WhisperForCTC from openai +author: John Snow Labs +name: asr_whisper_base +date: 2023-10-17 +tags: [whisper, xx, open_source, asr, onnx] +task: Automatic Speech Recognition +language: xx +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_base` is a Multilingual model originally trained by openai. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_base_xx_5.1.4_3.4_1697580471843.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_base_xx_5.1.4_3.4_1697580471843.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_base","xx") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_base","xx") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_base| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|xx| +|Size:|398.5 MB| + +## References + +https://huggingface.co/openai/whisper-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_kannada_base_kn.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_kannada_base_kn.md new file mode 100644 index 00000000000000..249c03a8c2b041 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_kannada_base_kn.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Kannada asr_whisper_kannada_base WhisperForCTC from vasista22 +author: John Snow Labs +name: asr_whisper_kannada_base +date: 2023-10-17 +tags: [whisper, kn, open_source, asr, onnx] +task: Automatic Speech Recognition +language: kn +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_kannada_base` is a Kannada model originally trained by vasista22. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_kannada_base_kn_5.1.4_3.4_1697579492668.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_kannada_base_kn_5.1.4_3.4_1697579492668.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_kannada_base","kn") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_kannada_base","kn") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_kannada_base| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|kn| +|Size:|643.6 MB| + +## References + +https://huggingface.co/vasista22/whisper-kannada-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_kannada_base_pipeline_kn.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_kannada_base_pipeline_kn.md new file mode 100644 index 00000000000000..cdb95c44ee78eb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_kannada_base_pipeline_kn.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Kannada asr_whisper_kannada_base_pipeline pipeline WhisperForCTC from vasista22 +author: John Snow Labs +name: asr_whisper_kannada_base_pipeline +date: 2023-10-17 +tags: [whisper, kn, open_source, pipeline] +task: Automatic Speech Recognition +language: kn +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_kannada_base_pipeline` is a Kannada model originally trained by vasista22. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_kannada_base_pipeline_kn_5.1.4_3.4_1697579503990.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_kannada_base_pipeline_kn_5.1.4_3.4_1697579503990.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_kannada_base_pipeline', lang = 'kn') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_kannada_base_pipeline', lang = 'kn') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_kannada_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|kn| +|Size:|643.6 MB| + +## References + +https://huggingface.co/vasista22/whisper-kannada-base + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_kannada_small_kn.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_kannada_small_kn.md new file mode 100644 index 00000000000000..3d55acbe36bd2c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_kannada_small_kn.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Kannada asr_whisper_kannada_small WhisperForCTC from vasista22 +author: John Snow Labs +name: asr_whisper_kannada_small +date: 2023-10-17 +tags: [whisper, kn, open_source, asr, onnx] +task: Automatic Speech Recognition +language: kn +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_kannada_small` is a Kannada model originally trained by vasista22. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_kannada_small_kn_5.1.4_3.4_1697584952690.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_kannada_small_kn_5.1.4_3.4_1697584952690.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_kannada_small","kn") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_kannada_small","kn") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_kannada_small| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|kn| +|Size:|1.7 GB| + +## References + +https://huggingface.co/vasista22/whisper-kannada-small \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_kannada_small_pipeline_kn.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_kannada_small_pipeline_kn.md new file mode 100644 index 00000000000000..cbd81d8bba9900 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_kannada_small_pipeline_kn.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Kannada asr_whisper_kannada_small_pipeline pipeline WhisperForCTC from vasista22 +author: John Snow Labs +name: asr_whisper_kannada_small_pipeline +date: 2023-10-17 +tags: [whisper, kn, open_source, pipeline] +task: Automatic Speech Recognition +language: kn +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_kannada_small_pipeline` is a Kannada model originally trained by vasista22. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_kannada_small_pipeline_kn_5.1.4_3.4_1697584992461.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_kannada_small_pipeline_kn_5.1.4_3.4_1697584992461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_kannada_small_pipeline', lang = 'kn') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_kannada_small_pipeline', lang = 'kn') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_kannada_small_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|kn| +|Size:|1.7 GB| + +## References + +https://huggingface.co/vasista22/whisper-kannada-small + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_allsnr_de.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_allsnr_de.md new file mode 100644 index 00000000000000..37f2c980d8df0c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_allsnr_de.md @@ -0,0 +1,92 @@ +--- +layout: model +title: German asr_whisper_small_allsnr WhisperForCTC from marccgrau +author: John Snow Labs +name: asr_whisper_small_allsnr +date: 2023-10-17 +tags: [whisper, de, open_source, asr, onnx] +task: Automatic Speech Recognition +language: de +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_allsnr` is a German model originally trained by marccgrau. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_allsnr_de_5.1.4_3.4_1697581729008.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_allsnr_de_5.1.4_3.4_1697581729008.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_allsnr","de") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_allsnr","de") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_allsnr| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|de| +|Size:|1.7 GB| + +## References + +https://huggingface.co/marccgrau/whisper-small-allSNR \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_czech_cv11_cs.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_czech_cv11_cs.md new file mode 100644 index 00000000000000..d6669b16d3d931 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_czech_cv11_cs.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Czech asr_whisper_small_czech_cv11 WhisperForCTC from mikr +author: John Snow Labs +name: asr_whisper_small_czech_cv11 +date: 2023-10-17 +tags: [whisper, cs, open_source, asr, onnx] +task: Automatic Speech Recognition +language: cs +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_czech_cv11` is a Czech model originally trained by mikr. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_czech_cv11_cs_5.1.4_3.4_1697582051071.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_czech_cv11_cs_5.1.4_3.4_1697582051071.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_czech_cv11","cs") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_czech_cv11","cs") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_czech_cv11| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|cs| +|Size:|1.7 GB| + +## References + +https://huggingface.co/mikr/whisper-small-cs-cv11 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_czech_cv11_pipeline_cs.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_czech_cv11_pipeline_cs.md new file mode 100644 index 00000000000000..c101de18dae2d8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_czech_cv11_pipeline_cs.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Czech asr_whisper_small_czech_cv11_pipeline pipeline WhisperForCTC from mikr +author: John Snow Labs +name: asr_whisper_small_czech_cv11_pipeline +date: 2023-10-17 +tags: [whisper, cs, open_source, pipeline] +task: Automatic Speech Recognition +language: cs +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_czech_cv11_pipeline` is a Czech model originally trained by mikr. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_czech_cv11_pipeline_cs_5.1.4_3.4_1697582077518.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_czech_cv11_pipeline_cs_5.1.4_3.4_1697582077518.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_czech_cv11_pipeline', lang = 'cs') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_czech_cv11_pipeline', lang = 'cs') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_czech_cv11_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|cs| +|Size:|1.7 GB| + +## References + +https://huggingface.co/mikr/whisper-small-cs-cv11 + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized_fr.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized_fr.md new file mode 100644 index 00000000000000..ee95a957080895 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized_fr.md @@ -0,0 +1,92 @@ +--- +layout: model +title: French asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized WhisperForCTC from jwkritchie +author: John Snow Labs +name: asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized +date: 2023-10-17 +tags: [whisper, fr, open_source, asr, onnx] +task: Automatic Speech Recognition +language: fr +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized` is a French model originally trained by jwkritchie. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized_fr_5.1.4_3.4_1697582400007.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized_fr_5.1.4_3.4_1697582400007.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized","fr") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized","fr") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|fr| +|Size:|1.7 GB| + +## References + +https://huggingface.co/jwkritchie/whisper-small-defined-dot-ai-qc-fr-combined-dataset-normalized \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized_pipeline_fr.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized_pipeline_fr.md new file mode 100644 index 00000000000000..af6fb71125dc26 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized_pipeline_fr.md @@ -0,0 +1,71 @@ +--- +layout: model +title: French asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized_pipeline pipeline WhisperForCTC from jwkritchie +author: John Snow Labs +name: asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized_pipeline +date: 2023-10-17 +tags: [whisper, fr, open_source, pipeline] +task: Automatic Speech Recognition +language: fr +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized_pipeline` is a French model originally trained by jwkritchie. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized_pipeline_fr_5.1.4_3.4_1697582437910.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized_pipeline_fr_5.1.4_3.4_1697582437910.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized_pipeline', lang = 'fr') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized_pipeline', lang = 'fr') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_defined_dot_ai_qc_french_combined_dataset_normalized_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|fr| +|Size:|1.7 GB| + +## References + +https://huggingface.co/jwkritchie/whisper-small-defined-dot-ai-qc-fr-combined-dataset-normalized + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_english_en.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_english_en.md new file mode 100644 index 00000000000000..7ca7c8e4bfc62a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_english_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_small_english WhisperForCTC from openai +author: John Snow Labs +name: asr_whisper_small_english +date: 2023-10-17 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_english` is a English model originally trained by openai. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_english_en_5.1.4_3.4_1697585976463.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_english_en_5.1.4_3.4_1697585976463.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_english","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_english","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_english| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.1 GB| + +## References + +https://huggingface.co/openai/whisper-small.en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_english_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_english_pipeline_en.md new file mode 100644 index 00000000000000..ea00318a00079c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_english_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_small_english_pipeline pipeline WhisperForCTC from openai +author: John Snow Labs +name: asr_whisper_small_english_pipeline +date: 2023-10-17 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_english_pipeline` is a English model originally trained by openai. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_english_pipeline_en_5.1.4_3.4_1697585998441.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_english_pipeline_en_5.1.4_3.4_1697585998441.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_english_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_english_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.1 GB| + +## References + +https://huggingface.co/openai/whisper-small.en + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_greek_el.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_greek_el.md new file mode 100644 index 00000000000000..de68aeeaa98d68 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_greek_el.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Modern Greek (1453-) asr_whisper_small_greek WhisperForCTC from farsipal +author: John Snow Labs +name: asr_whisper_small_greek +date: 2023-10-17 +tags: [whisper, el, open_source, asr, onnx] +task: Automatic Speech Recognition +language: el +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_greek` is a Modern Greek (1453-) model originally trained by farsipal. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_greek_el_5.1.4_3.4_1697581262666.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_greek_el_5.1.4_3.4_1697581262666.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_greek","el") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_greek","el") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_greek| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|el| +|Size:|1.1 GB| + +## References + +https://huggingface.co/farsipal/whisper-small-greek \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_greek_pipeline_el.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_greek_pipeline_el.md new file mode 100644 index 00000000000000..dea0b3dc264e97 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_greek_pipeline_el.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Modern Greek (1453-) asr_whisper_small_greek_pipeline pipeline WhisperForCTC from farsipal +author: John Snow Labs +name: asr_whisper_small_greek_pipeline +date: 2023-10-17 +tags: [whisper, el, open_source, pipeline] +task: Automatic Speech Recognition +language: el +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_greek_pipeline` is a Modern Greek (1453-) model originally trained by farsipal. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_greek_pipeline_el_5.1.4_3.4_1697581283359.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_greek_pipeline_el_5.1.4_3.4_1697581283359.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_greek_pipeline', lang = 'el') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_greek_pipeline', lang = 'el') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_greek_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|el| +|Size:|1.1 GB| + +## References + +https://huggingface.co/farsipal/whisper-small-greek + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_italian_3_it.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_italian_3_it.md new file mode 100644 index 00000000000000..189b31544acbce --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_italian_3_it.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Italian asr_whisper_small_italian_3 WhisperForCTC from GIanlucaRub +author: John Snow Labs +name: asr_whisper_small_italian_3 +date: 2023-10-17 +tags: [whisper, it, open_source, asr, onnx] +task: Automatic Speech Recognition +language: it +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_italian_3` is a Italian model originally trained by GIanlucaRub. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_italian_3_it_5.1.4_3.4_1697586608746.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_italian_3_it_5.1.4_3.4_1697586608746.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_italian_3","it") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_italian_3","it") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_italian_3| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|it| +|Size:|1.7 GB| + +## References + +https://huggingface.co/GIanlucaRub/whisper-small-it-3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_italian_3_pipeline_it.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_italian_3_pipeline_it.md new file mode 100644 index 00000000000000..6246ac002b491b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_italian_3_pipeline_it.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Italian asr_whisper_small_italian_3_pipeline pipeline WhisperForCTC from GIanlucaRub +author: John Snow Labs +name: asr_whisper_small_italian_3_pipeline +date: 2023-10-17 +tags: [whisper, it, open_source, pipeline] +task: Automatic Speech Recognition +language: it +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_italian_3_pipeline` is a Italian model originally trained by GIanlucaRub. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_italian_3_pipeline_it_5.1.4_3.4_1697586635172.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_italian_3_pipeline_it_5.1.4_3.4_1697586635172.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_italian_3_pipeline', lang = 'it') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_italian_3_pipeline', lang = 'it') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_italian_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|it| +|Size:|1.7 GB| + +## References + +https://huggingface.co/GIanlucaRub/whisper-small-it-3 + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_mongolian_1_mn.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_mongolian_1_mn.md new file mode 100644 index 00000000000000..b338e04dd224cb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_mongolian_1_mn.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Mongolian asr_whisper_small_mongolian_1 WhisperForCTC from bayartsogt +author: John Snow Labs +name: asr_whisper_small_mongolian_1 +date: 2023-10-17 +tags: [whisper, mn, open_source, asr, onnx] +task: Automatic Speech Recognition +language: mn +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_mongolian_1` is a Mongolian model originally trained by bayartsogt. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_mongolian_1_mn_5.1.4_3.4_1697583892680.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_mongolian_1_mn_5.1.4_3.4_1697583892680.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_mongolian_1","mn") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_mongolian_1","mn") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_mongolian_1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|mn| +|Size:|1.7 GB| + +## References + +https://huggingface.co/bayartsogt/whisper-small-mn-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_mongolian_1_pipeline_mn.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_mongolian_1_pipeline_mn.md new file mode 100644 index 00000000000000..0acbe5120db4c7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_mongolian_1_pipeline_mn.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Mongolian asr_whisper_small_mongolian_1_pipeline pipeline WhisperForCTC from bayartsogt +author: John Snow Labs +name: asr_whisper_small_mongolian_1_pipeline +date: 2023-10-17 +tags: [whisper, mn, open_source, pipeline] +task: Automatic Speech Recognition +language: mn +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_mongolian_1_pipeline` is a Mongolian model originally trained by bayartsogt. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_mongolian_1_pipeline_mn_5.1.4_3.4_1697583918301.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_mongolian_1_pipeline_mn_5.1.4_3.4_1697583918301.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_mongolian_1_pipeline', lang = 'mn') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_mongolian_1_pipeline', lang = 'mn') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_mongolian_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|mn| +|Size:|1.7 GB| + +## References + +https://huggingface.co/bayartsogt/whisper-small-mn-1 + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_mongolian_2_en.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_mongolian_2_en.md new file mode 100644 index 00000000000000..4dc6938ccd7899 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_mongolian_2_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_small_mongolian_2 WhisperForCTC from bayartsogt +author: John Snow Labs +name: asr_whisper_small_mongolian_2 +date: 2023-10-17 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_mongolian_2` is a English model originally trained by bayartsogt. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_mongolian_2_en_5.1.4_3.4_1697585749768.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_mongolian_2_en_5.1.4_3.4_1697585749768.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_mongolian_2","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_mongolian_2","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_mongolian_2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/bayartsogt/whisper-small-mn-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_mongolian_2_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_mongolian_2_pipeline_en.md new file mode 100644 index 00000000000000..3e14c5eb3dfe73 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_mongolian_2_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_small_mongolian_2_pipeline pipeline WhisperForCTC from bayartsogt +author: John Snow Labs +name: asr_whisper_small_mongolian_2_pipeline +date: 2023-10-17 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_mongolian_2_pipeline` is a English model originally trained by bayartsogt. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_mongolian_2_pipeline_en_5.1.4_3.4_1697585790673.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_mongolian_2_pipeline_en_5.1.4_3.4_1697585790673.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_mongolian_2_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_mongolian_2_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_mongolian_2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/bayartsogt/whisper-small-mn-2 + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_pipeline_xx.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_pipeline_xx.md new file mode 100644 index 00000000000000..32843da828f2c6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_pipeline_xx.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Multilingual asr_whisper_small_pipeline pipeline WhisperForCTC from openai +author: John Snow Labs +name: asr_whisper_small_pipeline +date: 2023-10-17 +tags: [whisper, xx, open_source, pipeline] +task: Automatic Speech Recognition +language: xx +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_pipeline` is a Multilingual model originally trained by openai. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_pipeline_xx_5.1.4_3.4_1697581725467.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_pipeline_xx_5.1.4_3.4_1697581725467.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_pipeline', lang = 'xx') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_pipeline', lang = 'xx') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|1.1 GB| + +## References + +https://huggingface.co/openai/whisper-small + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_se2_en.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_se2_en.md new file mode 100644 index 00000000000000..e5d21a5cc33028 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_se2_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_small_se2 WhisperForCTC from ayberkuckun +author: John Snow Labs +name: asr_whisper_small_se2 +date: 2023-10-17 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_se2` is a English model originally trained by ayberkuckun. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_se2_en_5.1.4_3.4_1697581369035.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_se2_en_5.1.4_3.4_1697581369035.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_se2","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_se2","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_se2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/ayberkuckun/whisper-small-se2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_se2_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_se2_pipeline_en.md new file mode 100644 index 00000000000000..9b51cc337a2dee --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_se2_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_small_se2_pipeline pipeline WhisperForCTC from ayberkuckun +author: John Snow Labs +name: asr_whisper_small_se2_pipeline +date: 2023-10-17 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_se2_pipeline` is a English model originally trained by ayberkuckun. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_se2_pipeline_en_5.1.4_3.4_1697581394596.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_se2_pipeline_en_5.1.4_3.4_1697581394596.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_se2_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_se2_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_se2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/ayberkuckun/whisper-small-se2 + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_swahili_pplantinga_pipeline_sw.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_swahili_pplantinga_pipeline_sw.md new file mode 100644 index 00000000000000..c5dc83b15a8702 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_swahili_pplantinga_pipeline_sw.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Swahili (macrolanguage) asr_whisper_small_swahili_pplantinga_pipeline pipeline WhisperForCTC from pplantinga +author: John Snow Labs +name: asr_whisper_small_swahili_pplantinga_pipeline +date: 2023-10-17 +tags: [whisper, sw, open_source, pipeline] +task: Automatic Speech Recognition +language: sw +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_swahili_pplantinga_pipeline` is a Swahili (macrolanguage) model originally trained by pplantinga. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swahili_pplantinga_pipeline_sw_5.1.4_3.4_1697580448260.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swahili_pplantinga_pipeline_sw_5.1.4_3.4_1697580448260.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_swahili_pplantinga_pipeline', lang = 'sw') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_swahili_pplantinga_pipeline', lang = 'sw') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_swahili_pplantinga_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|sw| +|Size:|1.7 GB| + +## References + +https://huggingface.co/pplantinga/whisper-small-sw + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_swahili_pplantinga_sw.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_swahili_pplantinga_sw.md new file mode 100644 index 00000000000000..d23af81147e281 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_swahili_pplantinga_sw.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Swahili (macrolanguage) asr_whisper_small_swahili_pplantinga WhisperForCTC from pplantinga +author: John Snow Labs +name: asr_whisper_small_swahili_pplantinga +date: 2023-10-17 +tags: [whisper, sw, open_source, asr, onnx] +task: Automatic Speech Recognition +language: sw +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_swahili_pplantinga` is a Swahili (macrolanguage) model originally trained by pplantinga. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swahili_pplantinga_sw_5.1.4_3.4_1697580424248.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swahili_pplantinga_sw_5.1.4_3.4_1697580424248.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_swahili_pplantinga","sw") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_swahili_pplantinga","sw") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_swahili_pplantinga| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|sw| +|Size:|1.7 GB| + +## References + +https://huggingface.co/pplantinga/whisper-small-sw \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_swe_davidt123_en.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_swe_davidt123_en.md new file mode 100644 index 00000000000000..bdc57dfc577c3c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_swe_davidt123_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_small_swe_davidt123 WhisperForCTC from davidt123 +author: John Snow Labs +name: asr_whisper_small_swe_davidt123 +date: 2023-10-17 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_swe_davidt123` is a English model originally trained by davidt123. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swe_davidt123_en_5.1.4_3.4_1697579793966.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swe_davidt123_en_5.1.4_3.4_1697579793966.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_swe_davidt123","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_swe_davidt123","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_swe_davidt123| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/davidt123/whisper_small_swe \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_swe_davidt123_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_swe_davidt123_pipeline_en.md new file mode 100644 index 00000000000000..edf7cc74882197 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_swe_davidt123_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_small_swe_davidt123_pipeline pipeline WhisperForCTC from davidt123 +author: John Snow Labs +name: asr_whisper_small_swe_davidt123_pipeline +date: 2023-10-17 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_swe_davidt123_pipeline` is a English model originally trained by davidt123. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swe_davidt123_pipeline_en_5.1.4_3.4_1697579817761.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swe_davidt123_pipeline_en_5.1.4_3.4_1697579817761.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_swe_davidt123_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_swe_davidt123_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_swe_davidt123_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/davidt123/whisper_small_swe + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_telugu_146h_pipeline_te.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_telugu_146h_pipeline_te.md new file mode 100644 index 00000000000000..8abe6232b55a7a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_telugu_146h_pipeline_te.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Telugu asr_whisper_small_telugu_146h_pipeline pipeline WhisperForCTC from swechafsmi +author: John Snow Labs +name: asr_whisper_small_telugu_146h_pipeline +date: 2023-10-17 +tags: [whisper, te, open_source, pipeline] +task: Automatic Speech Recognition +language: te +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_telugu_146h_pipeline` is a Telugu model originally trained by swechafsmi. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_telugu_146h_pipeline_te_5.1.4_3.4_1697584130875.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_telugu_146h_pipeline_te_5.1.4_3.4_1697584130875.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_telugu_146h_pipeline', lang = 'te') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_telugu_146h_pipeline', lang = 'te') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_telugu_146h_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|te| +|Size:|1.7 GB| + +## References + +https://huggingface.co/swechafsmi/whisper-small-te-146h + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_telugu_146h_te.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_telugu_146h_te.md new file mode 100644 index 00000000000000..a24ebfd086e747 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_telugu_146h_te.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Telugu asr_whisper_small_telugu_146h WhisperForCTC from swechafsmi +author: John Snow Labs +name: asr_whisper_small_telugu_146h +date: 2023-10-17 +tags: [whisper, te, open_source, asr, onnx] +task: Automatic Speech Recognition +language: te +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_telugu_146h` is a Telugu model originally trained by swechafsmi. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_telugu_146h_te_5.1.4_3.4_1697584092998.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_telugu_146h_te_5.1.4_3.4_1697584092998.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_telugu_146h","te") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_telugu_146h","te") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_telugu_146h| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|te| +|Size:|1.7 GB| + +## References + +https://huggingface.co/swechafsmi/whisper-small-te-146h \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_telugu_openslr_en.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_telugu_openslr_en.md new file mode 100644 index 00000000000000..3cda2180c2d7fb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_telugu_openslr_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_small_telugu_openslr WhisperForCTC from yaswanth +author: John Snow Labs +name: asr_whisper_small_telugu_openslr +date: 2023-10-17 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_telugu_openslr` is a English model originally trained by yaswanth. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_telugu_openslr_en_5.1.4_3.4_1697584639657.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_telugu_openslr_en_5.1.4_3.4_1697584639657.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_telugu_openslr","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_telugu_openslr","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_telugu_openslr| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/yaswanth/whisper-small-te_openslr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_telugu_openslr_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_telugu_openslr_pipeline_en.md new file mode 100644 index 00000000000000..94089dc4732cce --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_telugu_openslr_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_small_telugu_openslr_pipeline pipeline WhisperForCTC from yaswanth +author: John Snow Labs +name: asr_whisper_small_telugu_openslr_pipeline +date: 2023-10-17 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_telugu_openslr_pipeline` is a English model originally trained by yaswanth. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_telugu_openslr_pipeline_en_5.1.4_3.4_1697584668923.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_telugu_openslr_pipeline_en_5.1.4_3.4_1697584668923.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_telugu_openslr_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_telugu_openslr_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_telugu_openslr_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/yaswanth/whisper-small-te_openslr + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_thai_napatswift_pipeline_th.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_thai_napatswift_pipeline_th.md new file mode 100644 index 00000000000000..17cd0f0f4882da --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_thai_napatswift_pipeline_th.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Thai asr_whisper_small_thai_napatswift_pipeline pipeline WhisperForCTC from napatswift +author: John Snow Labs +name: asr_whisper_small_thai_napatswift_pipeline +date: 2023-10-17 +tags: [whisper, th, open_source, pipeline] +task: Automatic Speech Recognition +language: th +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_thai_napatswift_pipeline` is a Thai model originally trained by napatswift. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_thai_napatswift_pipeline_th_5.1.4_3.4_1697583679102.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_thai_napatswift_pipeline_th_5.1.4_3.4_1697583679102.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_thai_napatswift_pipeline', lang = 'th') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_thai_napatswift_pipeline', lang = 'th') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_thai_napatswift_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|th| +|Size:|1.7 GB| + +## References + +https://huggingface.co/napatswift/whisper-small-thai + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_thai_napatswift_th.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_thai_napatswift_th.md new file mode 100644 index 00000000000000..5188725afc257f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_thai_napatswift_th.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Thai asr_whisper_small_thai_napatswift WhisperForCTC from napatswift +author: John Snow Labs +name: asr_whisper_small_thai_napatswift +date: 2023-10-17 +tags: [whisper, th, open_source, asr, onnx] +task: Automatic Speech Recognition +language: th +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_thai_napatswift` is a Thai model originally trained by napatswift. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_thai_napatswift_th_5.1.4_3.4_1697583642698.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_thai_napatswift_th_5.1.4_3.4_1697583642698.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_thai_napatswift","th") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_thai_napatswift","th") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_thai_napatswift| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|th| +|Size:|1.7 GB| + +## References + +https://huggingface.co/napatswift/whisper-small-thai \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_tonga_zambia_en.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_tonga_zambia_en.md new file mode 100644 index 00000000000000..3c8b094b986243 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_tonga_zambia_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_small_tonga_zambia WhisperForCTC from csikasote +author: John Snow Labs +name: asr_whisper_small_tonga_zambia +date: 2023-10-17 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_tonga_zambia` is a English model originally trained by csikasote. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_tonga_zambia_en_5.1.4_3.4_1697579942341.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_tonga_zambia_en_5.1.4_3.4_1697579942341.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_tonga_zambia","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_tonga_zambia","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_tonga_zambia| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/csikasote/whisper-small-toi \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_tonga_zambia_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_tonga_zambia_pipeline_en.md new file mode 100644 index 00000000000000..fb07768f6e0efa --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_tonga_zambia_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_small_tonga_zambia_pipeline pipeline WhisperForCTC from csikasote +author: John Snow Labs +name: asr_whisper_small_tonga_zambia_pipeline +date: 2023-10-17 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_tonga_zambia_pipeline` is a English model originally trained by csikasote. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_tonga_zambia_pipeline_en_5.1.4_3.4_1697579965854.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_tonga_zambia_pipeline_en_5.1.4_3.4_1697579965854.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_tonga_zambia_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_tonga_zambia_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_tonga_zambia_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/csikasote/whisper-small-toi + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_ukrainian_pipeline_uk.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_ukrainian_pipeline_uk.md new file mode 100644 index 00000000000000..e4f431f9dd8eb6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_ukrainian_pipeline_uk.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Ukrainian asr_whisper_small_ukrainian_pipeline pipeline WhisperForCTC from Yehor +author: John Snow Labs +name: asr_whisper_small_ukrainian_pipeline +date: 2023-10-17 +tags: [whisper, uk, open_source, pipeline] +task: Automatic Speech Recognition +language: uk +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_ukrainian_pipeline` is a Ukrainian model originally trained by Yehor. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_ukrainian_pipeline_uk_5.1.4_3.4_1697585787241.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_ukrainian_pipeline_uk_5.1.4_3.4_1697585787241.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_ukrainian_pipeline', lang = 'uk') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_ukrainian_pipeline', lang = 'uk') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_ukrainian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|uk| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Yehor/whisper-small-ukrainian + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_ukrainian_uk.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_ukrainian_uk.md new file mode 100644 index 00000000000000..fbd5ca376fcaf6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_ukrainian_uk.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Ukrainian asr_whisper_small_ukrainian WhisperForCTC from Yehor +author: John Snow Labs +name: asr_whisper_small_ukrainian +date: 2023-10-17 +tags: [whisper, uk, open_source, asr, onnx] +task: Automatic Speech Recognition +language: uk +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_ukrainian` is a Ukrainian model originally trained by Yehor. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_ukrainian_uk_5.1.4_3.4_1697585753181.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_ukrainian_uk_5.1.4_3.4_1697585753181.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_ukrainian","uk") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_ukrainian","uk") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_ukrainian| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|uk| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Yehor/whisper-small-ukrainian \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_xx.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_xx.md new file mode 100644 index 00000000000000..429e59c1d7865c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_small_xx.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Multilingual asr_whisper_small WhisperForCTC from openai +author: John Snow Labs +name: asr_whisper_small +date: 2023-10-17 +tags: [whisper, xx, open_source, asr, onnx] +task: Automatic Speech Recognition +language: xx +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small` is a Multilingual model originally trained by openai. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_xx_5.1.4_3.4_1697581706186.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_xx_5.1.4_3.4_1697581706186.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small","xx") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small","xx") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|xx| +|Size:|1.1 GB| + +## References + +https://huggingface.co/openai/whisper-small \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_telugu_tiny_pipeline_te.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_telugu_tiny_pipeline_te.md new file mode 100644 index 00000000000000..73232f0894e22b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_telugu_tiny_pipeline_te.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Telugu asr_whisper_telugu_tiny_pipeline pipeline WhisperForCTC from vasista22 +author: John Snow Labs +name: asr_whisper_telugu_tiny_pipeline +date: 2023-10-17 +tags: [whisper, te, open_source, pipeline] +task: Automatic Speech Recognition +language: te +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_telugu_tiny_pipeline` is a Telugu model originally trained by vasista22. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_telugu_tiny_pipeline_te_5.1.4_3.4_1697585640379.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_telugu_tiny_pipeline_te_5.1.4_3.4_1697585640379.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_telugu_tiny_pipeline', lang = 'te') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_telugu_tiny_pipeline', lang = 'te') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_telugu_tiny_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|te| +|Size:|391.1 MB| + +## References + +https://huggingface.co/vasista22/whisper-telugu-tiny + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_telugu_tiny_te.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_telugu_tiny_te.md new file mode 100644 index 00000000000000..11e68714886043 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_telugu_tiny_te.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Telugu asr_whisper_telugu_tiny WhisperForCTC from vasista22 +author: John Snow Labs +name: asr_whisper_telugu_tiny +date: 2023-10-17 +tags: [whisper, te, open_source, asr, onnx] +task: Automatic Speech Recognition +language: te +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_telugu_tiny` is a Telugu model originally trained by vasista22. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_telugu_tiny_te_5.1.4_3.4_1697585633821.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_telugu_tiny_te_5.1.4_3.4_1697585633821.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_telugu_tiny","te") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_telugu_tiny","te") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_telugu_tiny| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|te| +|Size:|391.1 MB| + +## References + +https://huggingface.co/vasista22/whisper-telugu-tiny \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_bulgarian_l_bg.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_bulgarian_l_bg.md new file mode 100644 index 00000000000000..9d31bd14f5c26d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_bulgarian_l_bg.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Bulgarian asr_whisper_tiny_bulgarian_l WhisperForCTC from nandovallec +author: John Snow Labs +name: asr_whisper_tiny_bulgarian_l +date: 2023-10-17 +tags: [whisper, bg, open_source, asr, onnx] +task: Automatic Speech Recognition +language: bg +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_bulgarian_l` is a Bulgarian model originally trained by nandovallec. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_bulgarian_l_bg_5.1.4_3.4_1697584004963.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_bulgarian_l_bg_5.1.4_3.4_1697584004963.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_bulgarian_l","bg") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_bulgarian_l","bg") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_bulgarian_l| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|bg| +|Size:|390.8 MB| + +## References + +https://huggingface.co/nandovallec/whisper-tiny-bg-l \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_bulgarian_l_pipeline_bg.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_bulgarian_l_pipeline_bg.md new file mode 100644 index 00000000000000..2cdbf913e19c27 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_bulgarian_l_pipeline_bg.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Bulgarian asr_whisper_tiny_bulgarian_l_pipeline pipeline WhisperForCTC from nandovallec +author: John Snow Labs +name: asr_whisper_tiny_bulgarian_l_pipeline +date: 2023-10-17 +tags: [whisper, bg, open_source, pipeline] +task: Automatic Speech Recognition +language: bg +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_bulgarian_l_pipeline` is a Bulgarian model originally trained by nandovallec. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_bulgarian_l_pipeline_bg_5.1.4_3.4_1697584012326.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_bulgarian_l_pipeline_bg_5.1.4_3.4_1697584012326.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_tiny_bulgarian_l_pipeline', lang = 'bg') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_tiny_bulgarian_l_pipeline', lang = 'bg') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_bulgarian_l_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|bg| +|Size:|390.9 MB| + +## References + +https://huggingface.co/nandovallec/whisper-tiny-bg-l + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_english_en.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_english_en.md new file mode 100644 index 00000000000000..0149580837cad7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_english_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_tiny_english WhisperForCTC from openai +author: John Snow Labs +name: asr_whisper_tiny_english +date: 2023-10-17 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_english` is a English model originally trained by openai. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_english_en_5.1.4_3.4_1697584049145.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_english_en_5.1.4_3.4_1697584049145.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_english","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_english","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_english| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|250.5 MB| + +## References + +https://huggingface.co/openai/whisper-tiny.en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_english_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_english_pipeline_en.md new file mode 100644 index 00000000000000..c1b4f15d2583db --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_english_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_tiny_english_pipeline pipeline WhisperForCTC from openai +author: John Snow Labs +name: asr_whisper_tiny_english_pipeline +date: 2023-10-17 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_english_pipeline` is a English model originally trained by openai. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_english_pipeline_en_5.1.4_3.4_1697584055654.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_english_pipeline_en_5.1.4_3.4_1697584055654.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_tiny_english_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_tiny_english_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|250.5 MB| + +## References + +https://huggingface.co/openai/whisper-tiny.en + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_pashto_en.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_pashto_en.md new file mode 100644 index 00000000000000..040d8654b2e840 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_pashto_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_tiny_pashto WhisperForCTC from ihanif +author: John Snow Labs +name: asr_whisper_tiny_pashto +date: 2023-10-17 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_pashto` is a English model originally trained by ihanif. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_pashto_en_5.1.4_3.4_1697587144404.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_pashto_en_5.1.4_3.4_1697587144404.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_pashto","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_pashto","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_pashto| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|391.0 MB| + +## References + +https://huggingface.co/ihanif/whisper-tiny-ps \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_pashto_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_pashto_pipeline_en.md new file mode 100644 index 00000000000000..35185350e71742 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_pashto_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_tiny_pashto_pipeline pipeline WhisperForCTC from ihanif +author: John Snow Labs +name: asr_whisper_tiny_pashto_pipeline +date: 2023-10-17 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_pashto_pipeline` is a English model originally trained by ihanif. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_pashto_pipeline_en_5.1.4_3.4_1697587150066.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_pashto_pipeline_en_5.1.4_3.4_1697587150066.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_tiny_pashto_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_tiny_pashto_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_pashto_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|391.0 MB| + +## References + +https://huggingface.co/ihanif/whisper-tiny-ps + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_pipeline_xx.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_pipeline_xx.md new file mode 100644 index 00000000000000..4ee650e1f2900e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_pipeline_xx.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Multilingual asr_whisper_tiny_pipeline pipeline WhisperForCTC from openai +author: John Snow Labs +name: asr_whisper_tiny_pipeline +date: 2023-10-17 +tags: [whisper, xx, open_source, pipeline] +task: Automatic Speech Recognition +language: xx +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_pipeline` is a Multilingual model originally trained by openai. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_pipeline_xx_5.1.4_3.4_1697579837137.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_pipeline_xx_5.1.4_3.4_1697579837137.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_tiny_pipeline', lang = 'xx') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_tiny_pipeline', lang = 'xx') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|242.8 MB| + +## References + +https://huggingface.co/openai/whisper-tiny + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_xx.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_xx.md new file mode 100644 index 00000000000000..dc97e6b39d830a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tiny_xx.md @@ -0,0 +1,109 @@ +--- +layout: model +title: Official whisper-tiny +author: John Snow Labs +name: asr_whisper_tiny +date: 2023-10-17 +tags: [whisper, en, audio, open_source, asr, xx, onnx] +task: Automatic Speech Recognition +language: xx +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Official pretrained Whisper model, adapted from HuggingFace transformer and curated to provide scalability and production-readiness using Spark NLP. + +This is a multilingual model and supports the following languages: + +Afrikaans, Arabic, Armenian, Azerbaijani, Belarusian, Bosnian, Bulgarian, Catalan, Chinese, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, Galician, German, Greek, Hebrew, Hindi, Hungarian, Icelandic, Indonesian, Italian, Japanese, Kannada, Kazakh, Korean, Latvian, Lithuanian, Macedonian, Malay, Marathi, Maori, Nepali, Norwegian, Persian, Polish, Portuguese, Romanian, Russian, Serbian, Slovak, Slovenian, Spanish, Swahili, Swedish, Tagalog, Tamil, Thai, Turkish, Ukrainian, Urdu, Vietnamese, and Welsh. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_xx_5.1.4_3.4_1697579830675.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_xx_5.1.4_3.4_1697579830675.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +import sparknlp +from sparknlp.base import * +from sparknlp.annotator import * +from pyspark.ml import Pipeline + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("asr_whisper_tiny", "xx") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +processedAudioFloats = spark.createDataFrame([[rawFloats]]).toDF("audio_content") +result = pipeline.fit(processedAudioFloats).transform(processedAudioFloats) +result.select("text.result").show(truncate = False) +``` +```scala +import spark.implicits._ +import com.johnsnowlabs.nlp.base._ +import com.johnsnowlabs.nlp.annotators._ +import com.johnsnowlabs.nlp.annotators.audio.WhisperForCTC +import org.apache.spark.ml.Pipeline + +val audioAssembler: AudioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText: WhisperForCTC = WhisperForCTC + .pretrained("asr_whisper_tiny", "xx") + .setInputCols("audio_assembler") + .setOutputCol("text") + +val pipeline: Pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val bufferedSource = + scala.io.Source.fromFile("src/test/resources/audio/txt/librispeech_asr_0.txt") + +val rawFloats = bufferedSource + .getLines() + .map(_.split(",").head.trim.toFloat) + .toArray +bufferedSource.close + +val processedAudioFloats = Seq(rawFloats).toDF("audio_content") + +val result = pipeline.fit(processedAudioFloats).transform(processedAudioFloats) +result.select("text.result").show(truncate = false) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|xx| +|Size:|242.8 MB| \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tswana_greek_modern_e1_el.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tswana_greek_modern_e1_el.md new file mode 100644 index 00000000000000..048b327e231471 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tswana_greek_modern_e1_el.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Modern Greek (1453-) asr_whisper_tswana_greek_modern_e1 WhisperForCTC from emilios +author: John Snow Labs +name: asr_whisper_tswana_greek_modern_e1 +date: 2023-10-17 +tags: [whisper, el, open_source, asr, onnx] +task: Automatic Speech Recognition +language: el +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tswana_greek_modern_e1` is a Modern Greek (1453-) model originally trained by emilios. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tswana_greek_modern_e1_el_5.1.4_3.4_1697583402368.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tswana_greek_modern_e1_el_5.1.4_3.4_1697583402368.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_tswana_greek_modern_e1","el") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_tswana_greek_modern_e1","el") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tswana_greek_modern_e1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|el| +|Size:|241.6 MB| + +## References + +https://huggingface.co/emilios/whisper-tn-el-e1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tswana_greek_modern_e1_pipeline_el.md b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tswana_greek_modern_e1_pipeline_el.md new file mode 100644 index 00000000000000..c1a3b2a3b05cb5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-17-asr_whisper_tswana_greek_modern_e1_pipeline_el.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Modern Greek (1453-) asr_whisper_tswana_greek_modern_e1_pipeline pipeline WhisperForCTC from emilios +author: John Snow Labs +name: asr_whisper_tswana_greek_modern_e1_pipeline +date: 2023-10-17 +tags: [whisper, el, open_source, pipeline] +task: Automatic Speech Recognition +language: el +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tswana_greek_modern_e1_pipeline` is a Modern Greek (1453-) model originally trained by emilios. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tswana_greek_modern_e1_pipeline_el_5.1.4_3.4_1697583407910.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tswana_greek_modern_e1_pipeline_el_5.1.4_3.4_1697583407910.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_tswana_greek_modern_e1_pipeline', lang = 'el') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_tswana_greek_modern_e1_pipeline', lang = 'el') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tswana_greek_modern_e1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|el| +|Size:|241.6 MB| + +## References + +https://huggingface.co/emilios/whisper-tn-el-e1 + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_base_bengali_trans_pipeline_xx.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_base_bengali_trans_pipeline_xx.md new file mode 100644 index 00000000000000..92fcd6ede87251 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_base_bengali_trans_pipeline_xx.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Multilingual asr_whisper_base_bengali_trans_pipeline pipeline WhisperForCTC from arijitx +author: John Snow Labs +name: asr_whisper_base_bengali_trans_pipeline +date: 2023-10-18 +tags: [whisper, xx, open_source, pipeline] +task: Automatic Speech Recognition +language: xx +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_base_bengali_trans_pipeline` is a Multilingual model originally trained by arijitx. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_base_bengali_trans_pipeline_xx_5.1.4_3.4_1697588822232.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_base_bengali_trans_pipeline_xx_5.1.4_3.4_1697588822232.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_base_bengali_trans_pipeline', lang = 'xx') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_base_bengali_trans_pipeline', lang = 'xx') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_base_bengali_trans_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|616.9 MB| + +## References + +https://huggingface.co/arijitx/whisper-base-bn-trans + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_base_bengali_trans_xx.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_base_bengali_trans_xx.md new file mode 100644 index 00000000000000..2bdb45829c7441 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_base_bengali_trans_xx.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Multilingual asr_whisper_base_bengali_trans WhisperForCTC from arijitx +author: John Snow Labs +name: asr_whisper_base_bengali_trans +date: 2023-10-18 +tags: [whisper, xx, open_source, asr, onnx] +task: Automatic Speech Recognition +language: xx +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_base_bengali_trans` is a Multilingual model originally trained by arijitx. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_base_bengali_trans_xx_5.1.4_3.4_1697588807282.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_base_bengali_trans_xx_5.1.4_3.4_1697588807282.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_base_bengali_trans","xx") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_base_bengali_trans","xx") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_base_bengali_trans| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|xx| +|Size:|616.9 MB| + +## References + +https://huggingface.co/arijitx/whisper-base-bn-trans \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_base_european_en.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_base_european_en.md new file mode 100644 index 00000000000000..16de96f10dab1d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_base_european_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_base_european WhisperForCTC from aware-ai +author: John Snow Labs +name: asr_whisper_base_european +date: 2023-10-18 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_base_european` is a English model originally trained by aware-ai. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_base_european_en_5.1.4_3.4_1697621307187.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_base_european_en_5.1.4_3.4_1697621307187.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_base_european","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_base_european","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_base_european| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|643.2 MB| + +## References + +https://huggingface.co/aware-ai/whisper-base-european \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_base_european_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_base_european_pipeline_en.md new file mode 100644 index 00000000000000..57982910350916 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_base_european_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_base_european_pipeline pipeline WhisperForCTC from aware-ai +author: John Snow Labs +name: asr_whisper_base_european_pipeline +date: 2023-10-18 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_base_european_pipeline` is a English model originally trained by aware-ai. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_base_european_pipeline_en_5.1.4_3.4_1697621319699.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_base_european_pipeline_en_5.1.4_3.4_1697621319699.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_base_european_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_base_european_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_base_european_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|643.2 MB| + +## References + +https://huggingface.co/aware-ai/whisper-base-european + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_base_pipeline_xx.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_base_pipeline_xx.md new file mode 100644 index 00000000000000..8c490bfadcf2c9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_base_pipeline_xx.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Multilingual asr_whisper_base_pipeline pipeline WhisperForCTC from openai +author: John Snow Labs +name: asr_whisper_base_pipeline +date: 2023-10-18 +tags: [whisper, xx, open_source, pipeline] +task: Automatic Speech Recognition +language: xx +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_base_pipeline` is a Multilingual model originally trained by openai. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_base_pipeline_xx_5.1.4_3.4_1697617598741.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_base_pipeline_xx_5.1.4_3.4_1697617598741.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_base_pipeline', lang = 'xx') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_base_pipeline', lang = 'xx') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_base_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|398.5 MB| + +## References + +https://huggingface.co/openai/whisper-base + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_base_xx.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_base_xx.md new file mode 100644 index 00000000000000..47effc80e13f5d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_base_xx.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Multilingual asr_whisper_base WhisperForCTC from openai +author: John Snow Labs +name: asr_whisper_base +date: 2023-10-18 +tags: [whisper, xx, open_source, asr, onnx] +task: Automatic Speech Recognition +language: xx +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_base` is a Multilingual model originally trained by openai. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_base_xx_5.1.4_3.4_1697617589019.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_base_xx_5.1.4_3.4_1697617589019.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_base","xx") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_base","xx") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_base| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|xx| +|Size:|398.5 MB| + +## References + +https://huggingface.co/openai/whisper-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_persian_farsi_en.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_persian_farsi_en.md new file mode 100644 index 00000000000000..6adf6228e65ccc --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_persian_farsi_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_persian_farsi WhisperForCTC from Yasaman +author: John Snow Labs +name: asr_whisper_persian_farsi +date: 2023-10-18 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_persian_farsi` is a English model originally trained by Yasaman. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_persian_farsi_en_5.1.4_3.4_1697589012994.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_persian_farsi_en_5.1.4_3.4_1697589012994.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_persian_farsi","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_persian_farsi","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_persian_farsi| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Yasaman/whisper_fa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_persian_farsi_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_persian_farsi_pipeline_en.md new file mode 100644 index 00000000000000..7a56dfb1c75c86 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_persian_farsi_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_persian_farsi_pipeline pipeline WhisperForCTC from Yasaman +author: John Snow Labs +name: asr_whisper_persian_farsi_pipeline +date: 2023-10-18 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_persian_farsi_pipeline` is a English model originally trained by Yasaman. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_persian_farsi_pipeline_en_5.1.4_3.4_1697589037917.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_persian_farsi_pipeline_en_5.1.4_3.4_1697589037917.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_persian_farsi_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_persian_farsi_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_persian_farsi_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Yasaman/whisper_fa + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_samoan_farsipal_e5_el.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_samoan_farsipal_e5_el.md new file mode 100644 index 00000000000000..fd181f684a9b51 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_samoan_farsipal_e5_el.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Modern Greek (1453-) asr_whisper_samoan_farsipal_e5 WhisperForCTC from emilios +author: John Snow Labs +name: asr_whisper_samoan_farsipal_e5 +date: 2023-10-18 +tags: [whisper, el, open_source, asr, onnx] +task: Automatic Speech Recognition +language: el +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_samoan_farsipal_e5` is a Modern Greek (1453-) model originally trained by emilios. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_samoan_farsipal_e5_el_5.1.4_3.4_1697589671565.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_samoan_farsipal_e5_el_5.1.4_3.4_1697589671565.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_samoan_farsipal_e5","el") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_samoan_farsipal_e5","el") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_samoan_farsipal_e5| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|el| +|Size:|1.1 GB| + +## References + +https://huggingface.co/emilios/whisper-sm-farsipal-e5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_samoan_farsipal_e5_pipeline_el.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_samoan_farsipal_e5_pipeline_el.md new file mode 100644 index 00000000000000..4667ffca58bd90 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_samoan_farsipal_e5_pipeline_el.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Modern Greek (1453-) asr_whisper_samoan_farsipal_e5_pipeline pipeline WhisperForCTC from emilios +author: John Snow Labs +name: asr_whisper_samoan_farsipal_e5_pipeline +date: 2023-10-18 +tags: [whisper, el, open_source, pipeline] +task: Automatic Speech Recognition +language: el +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_samoan_farsipal_e5_pipeline` is a Modern Greek (1453-) model originally trained by emilios. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_samoan_farsipal_e5_pipeline_el_5.1.4_3.4_1697589687809.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_samoan_farsipal_e5_pipeline_el_5.1.4_3.4_1697589687809.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_samoan_farsipal_e5_pipeline', lang = 'el') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_samoan_farsipal_e5_pipeline', lang = 'el') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_samoan_farsipal_e5_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|el| +|Size:|1.1 GB| + +## References + +https://huggingface.co/emilios/whisper-sm-farsipal-e5 + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_chinese_hk_en.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_chinese_hk_en.md new file mode 100644 index 00000000000000..4560809eeb3b33 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_chinese_hk_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_small_chinese_hk WhisperForCTC from tilos +author: John Snow Labs +name: asr_whisper_small_chinese_hk +date: 2023-10-18 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_chinese_hk` is a English model originally trained by tilos. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_chinese_hk_en_5.1.4_3.4_1697588775594.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_chinese_hk_en_5.1.4_3.4_1697588775594.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_chinese_hk","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_chinese_hk","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_chinese_hk| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/tilos/whisper-small-zh-HK \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_chinese_hk_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_chinese_hk_pipeline_en.md new file mode 100644 index 00000000000000..3f7208b48b1389 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_chinese_hk_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_small_chinese_hk_pipeline pipeline WhisperForCTC from tilos +author: John Snow Labs +name: asr_whisper_small_chinese_hk_pipeline +date: 2023-10-18 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_chinese_hk_pipeline` is a English model originally trained by tilos. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_chinese_hk_pipeline_en_5.1.4_3.4_1697588819567.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_chinese_hk_pipeline_en_5.1.4_3.4_1697588819567.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_chinese_hk_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_chinese_hk_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_chinese_hk_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/tilos/whisper-small-zh-HK + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_chinese_pipeline_zh.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_chinese_pipeline_zh.md new file mode 100644 index 00000000000000..0d8a6f89a54774 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_chinese_pipeline_zh.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Chinese asr_whisper_small_chinese_pipeline pipeline WhisperForCTC from xmzhu +author: John Snow Labs +name: asr_whisper_small_chinese_pipeline +date: 2023-10-18 +tags: [whisper, zh, open_source, pipeline] +task: Automatic Speech Recognition +language: zh +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_chinese_pipeline` is a Chinese model originally trained by xmzhu. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_chinese_pipeline_zh_5.1.4_3.4_1697587418263.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_chinese_pipeline_zh_5.1.4_3.4_1697587418263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_chinese_pipeline', lang = 'zh') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_chinese_pipeline', lang = 'zh') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_chinese_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|zh| +|Size:|1.7 GB| + +## References + +https://huggingface.co/xmzhu/whisper-small-zh + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_chinese_zh.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_chinese_zh.md new file mode 100644 index 00000000000000..91fb1e2509a46f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_chinese_zh.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Chinese asr_whisper_small_chinese WhisperForCTC from xmzhu +author: John Snow Labs +name: asr_whisper_small_chinese +date: 2023-10-18 +tags: [whisper, zh, open_source, asr, onnx] +task: Automatic Speech Recognition +language: zh +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_chinese` is a Chinese model originally trained by xmzhu. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_chinese_zh_5.1.4_3.4_1697587372288.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_chinese_zh_5.1.4_3.4_1697587372288.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_chinese","zh") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_chinese","zh") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_chinese| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|zh| +|Size:|1.7 GB| + +## References + +https://huggingface.co/xmzhu/whisper-small-zh \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_finnish_15k_samples_fi.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_finnish_15k_samples_fi.md new file mode 100644 index 00000000000000..46af7bb6576888 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_finnish_15k_samples_fi.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Finnish asr_whisper_small_finnish_15k_samples WhisperForCTC from RASMUS +author: John Snow Labs +name: asr_whisper_small_finnish_15k_samples +date: 2023-10-18 +tags: [whisper, fi, open_source, asr, onnx] +task: Automatic Speech Recognition +language: fi +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_finnish_15k_samples` is a Finnish model originally trained by RASMUS. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_finnish_15k_samples_fi_5.1.4_3.4_1697621153794.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_finnish_15k_samples_fi_5.1.4_3.4_1697621153794.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_finnish_15k_samples","fi") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_finnish_15k_samples","fi") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_finnish_15k_samples| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|fi| +|Size:|1.7 GB| + +## References + +https://huggingface.co/RASMUS/whisper-small-fi-15k_samples \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_finnish_15k_samples_pipeline_fi.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_finnish_15k_samples_pipeline_fi.md new file mode 100644 index 00000000000000..2d95841c450282 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_finnish_15k_samples_pipeline_fi.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Finnish asr_whisper_small_finnish_15k_samples_pipeline pipeline WhisperForCTC from RASMUS +author: John Snow Labs +name: asr_whisper_small_finnish_15k_samples_pipeline +date: 2023-10-18 +tags: [whisper, fi, open_source, pipeline] +task: Automatic Speech Recognition +language: fi +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_finnish_15k_samples_pipeline` is a Finnish model originally trained by RASMUS. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_finnish_15k_samples_pipeline_fi_5.1.4_3.4_1697621190478.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_finnish_15k_samples_pipeline_fi_5.1.4_3.4_1697621190478.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_finnish_15k_samples_pipeline', lang = 'fi') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_finnish_15k_samples_pipeline', lang = 'fi') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_finnish_15k_samples_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|fi| +|Size:|1.7 GB| + +## References + +https://huggingface.co/RASMUS/whisper-small-fi-15k_samples + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_german_en.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_german_en.md new file mode 100644 index 00000000000000..5450fac14573dd --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_german_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_small_german WhisperForCTC from aware-ai +author: John Snow Labs +name: asr_whisper_small_german +date: 2023-10-18 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_german` is a English model originally trained by aware-ai. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_german_en_5.1.4_3.4_1697588230786.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_german_en_5.1.4_3.4_1697588230786.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_german","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_german","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_german| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/aware-ai/whisper-small-german \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_german_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_german_pipeline_en.md new file mode 100644 index 00000000000000..445ef5bf812cfc --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_german_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_small_german_pipeline pipeline WhisperForCTC from aware-ai +author: John Snow Labs +name: asr_whisper_small_german_pipeline +date: 2023-10-18 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_german_pipeline` is a English model originally trained by aware-ai. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_german_pipeline_en_5.1.4_3.4_1697588261636.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_german_pipeline_en_5.1.4_3.4_1697588261636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_german_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_german_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_german_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/aware-ai/whisper-small-german + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_hindi_norwegian_tensorboard_hi.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_hindi_norwegian_tensorboard_hi.md new file mode 100644 index 00000000000000..68e4eb9037c67d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_hindi_norwegian_tensorboard_hi.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Hindi asr_whisper_small_hindi_norwegian_tensorboard WhisperForCTC from sanchit-gandhi +author: John Snow Labs +name: asr_whisper_small_hindi_norwegian_tensorboard +date: 2023-10-18 +tags: [whisper, hi, open_source, asr, onnx] +task: Automatic Speech Recognition +language: hi +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_hindi_norwegian_tensorboard` is a Hindi model originally trained by sanchit-gandhi. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_hindi_norwegian_tensorboard_hi_5.1.4_3.4_1697589700658.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_hindi_norwegian_tensorboard_hi_5.1.4_3.4_1697589700658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_hindi_norwegian_tensorboard","hi") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_hindi_norwegian_tensorboard","hi") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_hindi_norwegian_tensorboard| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|hi| +|Size:|1.7 GB| + +## References + +https://huggingface.co/sanchit-gandhi/whisper-small-hi-no-tensorboard \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_hindi_norwegian_tensorboard_pipeline_hi.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_hindi_norwegian_tensorboard_pipeline_hi.md new file mode 100644 index 00000000000000..d6571bd8cb5682 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_hindi_norwegian_tensorboard_pipeline_hi.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Hindi asr_whisper_small_hindi_norwegian_tensorboard_pipeline pipeline WhisperForCTC from sanchit-gandhi +author: John Snow Labs +name: asr_whisper_small_hindi_norwegian_tensorboard_pipeline +date: 2023-10-18 +tags: [whisper, hi, open_source, pipeline] +task: Automatic Speech Recognition +language: hi +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_hindi_norwegian_tensorboard_pipeline` is a Hindi model originally trained by sanchit-gandhi. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_hindi_norwegian_tensorboard_pipeline_hi_5.1.4_3.4_1697589736295.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_hindi_norwegian_tensorboard_pipeline_hi_5.1.4_3.4_1697589736295.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_hindi_norwegian_tensorboard_pipeline', lang = 'hi') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_hindi_norwegian_tensorboard_pipeline', lang = 'hi') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_hindi_norwegian_tensorboard_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|hi| +|Size:|1.7 GB| + +## References + +https://huggingface.co/sanchit-gandhi/whisper-small-hi-no-tensorboard + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_hindi_shripadbhat_hi.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_hindi_shripadbhat_hi.md new file mode 100644 index 00000000000000..e21e8bde358e68 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_hindi_shripadbhat_hi.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Hindi asr_whisper_small_hindi_shripadbhat WhisperForCTC from shripadbhat +author: John Snow Labs +name: asr_whisper_small_hindi_shripadbhat +date: 2023-10-18 +tags: [whisper, hi, open_source, asr, onnx] +task: Automatic Speech Recognition +language: hi +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_hindi_shripadbhat` is a Hindi model originally trained by shripadbhat. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_hindi_shripadbhat_hi_5.1.4_3.4_1697587721228.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_hindi_shripadbhat_hi_5.1.4_3.4_1697587721228.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_hindi_shripadbhat","hi") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_hindi_shripadbhat","hi") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_hindi_shripadbhat| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|hi| +|Size:|1.7 GB| + +## References + +https://huggingface.co/shripadbhat/whisper-small-hi \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_hindi_shripadbhat_pipeline_hi.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_hindi_shripadbhat_pipeline_hi.md new file mode 100644 index 00000000000000..de4536f64abda8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_hindi_shripadbhat_pipeline_hi.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Hindi asr_whisper_small_hindi_shripadbhat_pipeline pipeline WhisperForCTC from shripadbhat +author: John Snow Labs +name: asr_whisper_small_hindi_shripadbhat_pipeline +date: 2023-10-18 +tags: [whisper, hi, open_source, pipeline] +task: Automatic Speech Recognition +language: hi +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_hindi_shripadbhat_pipeline` is a Hindi model originally trained by shripadbhat. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_hindi_shripadbhat_pipeline_hi_5.1.4_3.4_1697587754852.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_hindi_shripadbhat_pipeline_hi_5.1.4_3.4_1697587754852.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_hindi_shripadbhat_pipeline', lang = 'hi') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_hindi_shripadbhat_pipeline', lang = 'hi') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_hindi_shripadbhat_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|hi| +|Size:|1.7 GB| + +## References + +https://huggingface.co/shripadbhat/whisper-small-hi + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_japanese_jakeyoo_ja.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_japanese_jakeyoo_ja.md new file mode 100644 index 00000000000000..e0bf0e2cc7ba83 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_japanese_jakeyoo_ja.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Japanese asr_whisper_small_japanese_jakeyoo WhisperForCTC from jakeyoo +author: John Snow Labs +name: asr_whisper_small_japanese_jakeyoo +date: 2023-10-18 +tags: [whisper, ja, open_source, asr, onnx] +task: Automatic Speech Recognition +language: ja +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_japanese_jakeyoo` is a Japanese model originally trained by jakeyoo. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_japanese_jakeyoo_ja_5.1.4_3.4_1697589525110.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_japanese_jakeyoo_ja_5.1.4_3.4_1697589525110.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_japanese_jakeyoo","ja") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_japanese_jakeyoo","ja") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_japanese_jakeyoo| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|ja| +|Size:|1.7 GB| + +## References + +https://huggingface.co/jakeyoo/whisper-small-ja \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_japanese_jakeyoo_pipeline_ja.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_japanese_jakeyoo_pipeline_ja.md new file mode 100644 index 00000000000000..6cf962d2a068fd --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_japanese_jakeyoo_pipeline_ja.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Japanese asr_whisper_small_japanese_jakeyoo_pipeline pipeline WhisperForCTC from jakeyoo +author: John Snow Labs +name: asr_whisper_small_japanese_jakeyoo_pipeline +date: 2023-10-18 +tags: [whisper, ja, open_source, pipeline] +task: Automatic Speech Recognition +language: ja +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_japanese_jakeyoo_pipeline` is a Japanese model originally trained by jakeyoo. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_japanese_jakeyoo_pipeline_ja_5.1.4_3.4_1697589551194.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_japanese_jakeyoo_pipeline_ja_5.1.4_3.4_1697589551194.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_japanese_jakeyoo_pipeline', lang = 'ja') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_japanese_jakeyoo_pipeline', lang = 'ja') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_japanese_jakeyoo_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|ja| +|Size:|1.7 GB| + +## References + +https://huggingface.co/jakeyoo/whisper-small-ja + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_portuguese_yapeng_en.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_portuguese_yapeng_en.md new file mode 100644 index 00000000000000..f4c5f6198ce1e6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_portuguese_yapeng_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_small_portuguese_yapeng WhisperForCTC from Yapeng +author: John Snow Labs +name: asr_whisper_small_portuguese_yapeng +date: 2023-10-18 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_portuguese_yapeng` is a English model originally trained by Yapeng. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_portuguese_yapeng_en_5.1.4_3.4_1697620237483.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_portuguese_yapeng_en_5.1.4_3.4_1697620237483.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_portuguese_yapeng","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_portuguese_yapeng","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_portuguese_yapeng| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Yapeng/whisper-small-pt \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_portuguese_yapeng_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_portuguese_yapeng_pipeline_en.md new file mode 100644 index 00000000000000..4e16621fe478c4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_portuguese_yapeng_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_small_portuguese_yapeng_pipeline pipeline WhisperForCTC from Yapeng +author: John Snow Labs +name: asr_whisper_small_portuguese_yapeng_pipeline +date: 2023-10-18 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_portuguese_yapeng_pipeline` is a English model originally trained by Yapeng. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_portuguese_yapeng_pipeline_en_5.1.4_3.4_1697620263200.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_portuguese_yapeng_pipeline_en_5.1.4_3.4_1697620263200.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_portuguese_yapeng_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_portuguese_yapeng_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_portuguese_yapeng_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Yapeng/whisper-small-pt + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_swedish_bm_pipeline_sv.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_swedish_bm_pipeline_sv.md new file mode 100644 index 00000000000000..f9223ca23dfb97 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_swedish_bm_pipeline_sv.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Swedish asr_whisper_small_swedish_bm_pipeline pipeline WhisperForCTC from birgermoell +author: John Snow Labs +name: asr_whisper_small_swedish_bm_pipeline +date: 2023-10-18 +tags: [whisper, sv, open_source, pipeline] +task: Automatic Speech Recognition +language: sv +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_swedish_bm_pipeline` is a Swedish model originally trained by birgermoell. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swedish_bm_pipeline_sv_5.1.4_3.4_1697623575673.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swedish_bm_pipeline_sv_5.1.4_3.4_1697623575673.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_swedish_bm_pipeline', lang = 'sv') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_swedish_bm_pipeline', lang = 'sv') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_swedish_bm_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|sv| +|Size:|1.7 GB| + +## References + +https://huggingface.co/birgermoell/whisper-small-sv-bm + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_tatar_pipeline_tt.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_tatar_pipeline_tt.md new file mode 100644 index 00000000000000..2f92fd4cf50fb3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_tatar_pipeline_tt.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Tatar asr_whisper_small_tatar_pipeline pipeline WhisperForCTC from 501Good +author: John Snow Labs +name: asr_whisper_small_tatar_pipeline +date: 2023-10-18 +tags: [whisper, tt, open_source, pipeline] +task: Automatic Speech Recognition +language: tt +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_tatar_pipeline` is a Tatar model originally trained by 501Good. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_tatar_pipeline_tt_5.1.4_3.4_1697619326786.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_tatar_pipeline_tt_5.1.4_3.4_1697619326786.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_tatar_pipeline', lang = 'tt') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_tatar_pipeline', lang = 'tt') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_tatar_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|tt| +|Size:|1.7 GB| + +## References + +https://huggingface.co/501Good/whisper-small-tt + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_tatar_tt.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_tatar_tt.md new file mode 100644 index 00000000000000..6a99a3ac39e3f4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_tatar_tt.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Tatar asr_whisper_small_tatar WhisperForCTC from 501Good +author: John Snow Labs +name: asr_whisper_small_tatar +date: 2023-10-18 +tags: [whisper, tt, open_source, asr, onnx] +task: Automatic Speech Recognition +language: tt +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_tatar` is a Tatar model originally trained by 501Good. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_tatar_tt_5.1.4_3.4_1697619284915.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_tatar_tt_5.1.4_3.4_1697619284915.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_tatar","tt") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_tatar","tt") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_tatar| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|tt| +|Size:|1.7 GB| + +## References + +https://huggingface.co/501Good/whisper-small-tt \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_vietnamese_tuananh7198_pipeline_vi.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_vietnamese_tuananh7198_pipeline_vi.md new file mode 100644 index 00000000000000..e160d8993c8ec8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_vietnamese_tuananh7198_pipeline_vi.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Vietnamese asr_whisper_small_vietnamese_tuananh7198_pipeline pipeline WhisperForCTC from tuananh7198 +author: John Snow Labs +name: asr_whisper_small_vietnamese_tuananh7198_pipeline +date: 2023-10-18 +tags: [whisper, vi, open_source, pipeline] +task: Automatic Speech Recognition +language: vi +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_vietnamese_tuananh7198_pipeline` is a Vietnamese model originally trained by tuananh7198. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_vietnamese_tuananh7198_pipeline_vi_5.1.4_3.4_1697623445458.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_vietnamese_tuananh7198_pipeline_vi_5.1.4_3.4_1697623445458.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_vietnamese_tuananh7198_pipeline', lang = 'vi') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_vietnamese_tuananh7198_pipeline', lang = 'vi') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_vietnamese_tuananh7198_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|vi| +|Size:|1.7 GB| + +## References + +https://huggingface.co/tuananh7198/whisper-small-vi + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_vietnamese_tuananh7198_vi.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_vietnamese_tuananh7198_vi.md new file mode 100644 index 00000000000000..bdcab428b01420 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_small_vietnamese_tuananh7198_vi.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Vietnamese asr_whisper_small_vietnamese_tuananh7198 WhisperForCTC from tuananh7198 +author: John Snow Labs +name: asr_whisper_small_vietnamese_tuananh7198 +date: 2023-10-18 +tags: [whisper, vi, open_source, asr, onnx] +task: Automatic Speech Recognition +language: vi +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_vietnamese_tuananh7198` is a Vietnamese model originally trained by tuananh7198. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_vietnamese_tuananh7198_vi_5.1.4_3.4_1697623421456.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_vietnamese_tuananh7198_vi_5.1.4_3.4_1697623421456.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_vietnamese_tuananh7198","vi") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_vietnamese_tuananh7198","vi") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_vietnamese_tuananh7198| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|vi| +|Size:|1.7 GB| + +## References + +https://huggingface.co/tuananh7198/whisper-small-vi \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_european_en.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_european_en.md new file mode 100644 index 00000000000000..9a6ce8eca8cb6c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_european_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_tiny_european WhisperForCTC from aware-ai +author: John Snow Labs +name: asr_whisper_tiny_european +date: 2023-10-18 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_european` is a English model originally trained by aware-ai. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_european_en_5.1.4_3.4_1697633069323.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_european_en_5.1.4_3.4_1697633069323.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_european","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_european","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_european| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|390.9 MB| + +## References + +https://huggingface.co/aware-ai/whisper-tiny-european \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_european_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_european_pipeline_en.md new file mode 100644 index 00000000000000..835e9f6fe0c1ca --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_european_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_tiny_european_pipeline pipeline WhisperForCTC from aware-ai +author: John Snow Labs +name: asr_whisper_tiny_european_pipeline +date: 2023-10-18 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_european_pipeline` is a English model originally trained by aware-ai. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_european_pipeline_en_5.1.4_3.4_1697633088173.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_european_pipeline_en_5.1.4_3.4_1697633088173.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_tiny_european_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_tiny_european_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_european_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|390.9 MB| + +## References + +https://huggingface.co/aware-ai/whisper-tiny-european + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_german_en.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_german_en.md new file mode 100644 index 00000000000000..c158ff9b160bc7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_german_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_tiny_german WhisperForCTC from aware-ai +author: John Snow Labs +name: asr_whisper_tiny_german +date: 2023-10-18 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_german` is a English model originally trained by aware-ai. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_german_en_5.1.4_3.4_1697587339428.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_german_en_5.1.4_3.4_1697587339428.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_german","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_german","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_german| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|390.1 MB| + +## References + +https://huggingface.co/aware-ai/whisper-tiny-german \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_german_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_german_pipeline_en.md new file mode 100644 index 00000000000000..4218af892f3342 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_german_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_tiny_german_pipeline pipeline WhisperForCTC from aware-ai +author: John Snow Labs +name: asr_whisper_tiny_german_pipeline +date: 2023-10-18 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_german_pipeline` is a English model originally trained by aware-ai. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_german_pipeline_en_5.1.4_3.4_1697587348063.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_german_pipeline_en_5.1.4_3.4_1697587348063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_tiny_german_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_tiny_german_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_german_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|390.2 MB| + +## References + +https://huggingface.co/aware-ai/whisper-tiny-german + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_italian_1_it.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_italian_1_it.md new file mode 100644 index 00000000000000..9d7e966588bdf4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_italian_1_it.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Italian asr_whisper_tiny_italian_1 WhisperForCTC from GIanlucaRub +author: John Snow Labs +name: asr_whisper_tiny_italian_1 +date: 2023-10-18 +tags: [whisper, it, open_source, asr, onnx] +task: Automatic Speech Recognition +language: it +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_italian_1` is a Italian model originally trained by GIanlucaRub. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_italian_1_it_5.1.4_3.4_1697633094679.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_italian_1_it_5.1.4_3.4_1697633094679.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_italian_1","it") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_italian_1","it") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_italian_1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|it| +|Size:|390.7 MB| + +## References + +https://huggingface.co/GIanlucaRub/whisper-tiny-it-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_italian_1_pipeline_it.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_italian_1_pipeline_it.md new file mode 100644 index 00000000000000..3cec3cdd2e9153 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_italian_1_pipeline_it.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Italian asr_whisper_tiny_italian_1_pipeline pipeline WhisperForCTC from GIanlucaRub +author: John Snow Labs +name: asr_whisper_tiny_italian_1_pipeline +date: 2023-10-18 +tags: [whisper, it, open_source, pipeline] +task: Automatic Speech Recognition +language: it +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_italian_1_pipeline` is a Italian model originally trained by GIanlucaRub. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_italian_1_pipeline_it_5.1.4_3.4_1697633103685.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_italian_1_pipeline_it_5.1.4_3.4_1697633103685.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_tiny_italian_1_pipeline', lang = 'it') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_tiny_italian_1_pipeline', lang = 'it') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_italian_1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|it| +|Size:|390.7 MB| + +## References + +https://huggingface.co/GIanlucaRub/whisper-tiny-it-1 + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_pipeline_xx.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_pipeline_xx.md new file mode 100644 index 00000000000000..83a249175e449c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_pipeline_xx.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Multilingual asr_whisper_tiny_pipeline pipeline WhisperForCTC from openai +author: John Snow Labs +name: asr_whisper_tiny_pipeline +date: 2023-10-18 +tags: [whisper, xx, open_source, pipeline] +task: Automatic Speech Recognition +language: xx +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_pipeline` is a Multilingual model originally trained by openai. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_pipeline_xx_5.1.4_3.4_1697616957612.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_pipeline_xx_5.1.4_3.4_1697616957612.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_tiny_pipeline', lang = 'xx') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_tiny_pipeline', lang = 'xx') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|xx| +|Size:|242.8 MB| + +## References + +https://huggingface.co/openai/whisper-tiny + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_tamil_example_pipeline_ta.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_tamil_example_pipeline_ta.md new file mode 100644 index 00000000000000..024bd3bd1f6625 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_tamil_example_pipeline_ta.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Tamil asr_whisper_tiny_tamil_example_pipeline pipeline WhisperForCTC from parambharat +author: John Snow Labs +name: asr_whisper_tiny_tamil_example_pipeline +date: 2023-10-18 +tags: [whisper, ta, open_source, pipeline] +task: Automatic Speech Recognition +language: ta +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_tamil_example_pipeline` is a Tamil model originally trained by parambharat. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_tamil_example_pipeline_ta_5.1.4_3.4_1697590385878.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_tamil_example_pipeline_ta_5.1.4_3.4_1697590385878.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_tiny_tamil_example_pipeline', lang = 'ta') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_tiny_tamil_example_pipeline', lang = 'ta') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_tamil_example_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|ta| +|Size:|390.9 MB| + +## References + +https://huggingface.co/parambharat/whisper-tiny-ta-example + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_tamil_example_ta.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_tamil_example_ta.md new file mode 100644 index 00000000000000..4826475ea66d13 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_tamil_example_ta.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Tamil asr_whisper_tiny_tamil_example WhisperForCTC from parambharat +author: John Snow Labs +name: asr_whisper_tiny_tamil_example +date: 2023-10-18 +tags: [whisper, ta, open_source, asr, onnx] +task: Automatic Speech Recognition +language: ta +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_tamil_example` is a Tamil model originally trained by parambharat. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_tamil_example_ta_5.1.4_3.4_1697590379193.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_tamil_example_ta_5.1.4_3.4_1697590379193.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_tamil_example","ta") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_tamil_example","ta") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_tamil_example| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|ta| +|Size:|390.9 MB| + +## References + +https://huggingface.co/parambharat/whisper-tiny-ta-example \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_tgl_en.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_tgl_en.md new file mode 100644 index 00000000000000..c25914ecd13281 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_tgl_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_tiny_tgl WhisperForCTC from marcderbauer +author: John Snow Labs +name: asr_whisper_tiny_tgl +date: 2023-10-18 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_tgl` is a English model originally trained by marcderbauer. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_tgl_en_5.1.4_3.4_1697601388622.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_tgl_en_5.1.4_3.4_1697601388622.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_tgl","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_tgl","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_tgl| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|390.8 MB| + +## References + +https://huggingface.co/marcderbauer/whisper-tiny-tgl \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_tgl_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_tgl_pipeline_en.md new file mode 100644 index 00000000000000..d52691044ef227 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_tgl_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_tiny_tgl_pipeline pipeline WhisperForCTC from marcderbauer +author: John Snow Labs +name: asr_whisper_tiny_tgl_pipeline +date: 2023-10-18 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_tgl_pipeline` is a English model originally trained by marcderbauer. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_tgl_pipeline_en_5.1.4_3.4_1697601395684.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_tgl_pipeline_en_5.1.4_3.4_1697601395684.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_tiny_tgl_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_tiny_tgl_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_tgl_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|390.8 MB| + +## References + +https://huggingface.co/marcderbauer/whisper-tiny-tgl + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_xx.md b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_xx.md new file mode 100644 index 00000000000000..9dee88b49d3574 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-18-asr_whisper_tiny_xx.md @@ -0,0 +1,109 @@ +--- +layout: model +title: Official whisper-tiny +author: John Snow Labs +name: asr_whisper_tiny +date: 2023-10-18 +tags: [whisper, en, audio, open_source, asr, xx, onnx] +task: Automatic Speech Recognition +language: xx +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Official pretrained Whisper model, adapted from HuggingFace transformer and curated to provide scalability and production-readiness using Spark NLP. + +This is a multilingual model and supports the following languages: + +Afrikaans, Arabic, Armenian, Azerbaijani, Belarusian, Bosnian, Bulgarian, Catalan, Chinese, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, Galician, German, Greek, Hebrew, Hindi, Hungarian, Icelandic, Indonesian, Italian, Japanese, Kannada, Kazakh, Korean, Latvian, Lithuanian, Macedonian, Malay, Marathi, Maori, Nepali, Norwegian, Persian, Polish, Portuguese, Romanian, Russian, Serbian, Slovak, Slovenian, Spanish, Swahili, Swedish, Tagalog, Tamil, Thai, Turkish, Ukrainian, Urdu, Vietnamese, and Welsh. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_xx_5.1.4_3.4_1697616953370.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_xx_5.1.4_3.4_1697616953370.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +import sparknlp +from sparknlp.base import * +from sparknlp.annotator import * +from pyspark.ml import Pipeline + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + +speechToText = WhisperForCTC.pretrained("asr_whisper_tiny", "xx") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) +processedAudioFloats = spark.createDataFrame([[rawFloats]]).toDF("audio_content") +result = pipeline.fit(processedAudioFloats).transform(processedAudioFloats) +result.select("text.result").show(truncate = False) +``` +```scala +import spark.implicits._ +import com.johnsnowlabs.nlp.base._ +import com.johnsnowlabs.nlp.annotators._ +import com.johnsnowlabs.nlp.annotators.audio.WhisperForCTC +import org.apache.spark.ml.Pipeline + +val audioAssembler: AudioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText: WhisperForCTC = WhisperForCTC + .pretrained("asr_whisper_tiny", "xx") + .setInputCols("audio_assembler") + .setOutputCol("text") + +val pipeline: Pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val bufferedSource = + scala.io.Source.fromFile("src/test/resources/audio/txt/librispeech_asr_0.txt") + +val rawFloats = bufferedSource + .getLines() + .map(_.split(",").head.trim.toFloat) + .toArray +bufferedSource.close + +val processedAudioFloats = Seq(rawFloats).toDF("audio_content") + +val result = pipeline.fit(processedAudioFloats).transform(processedAudioFloats) +result.select("text.result").show(truncate = false) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|xx| +|Size:|242.8 MB| \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_personal_whisper_small_english_model_en.md b/docs/_posts/ahmedlone127/2023-10-19-asr_personal_whisper_small_english_model_en.md new file mode 100644 index 00000000000000..58c915b4449e4f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_personal_whisper_small_english_model_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_personal_whisper_small_english_model WhisperForCTC from fractalego +author: John Snow Labs +name: asr_personal_whisper_small_english_model +date: 2023-10-19 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_personal_whisper_small_english_model` is a English model originally trained by fractalego. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_personal_whisper_small_english_model_en_5.1.4_3.4_1697754481302.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_personal_whisper_small_english_model_en_5.1.4_3.4_1697754481302.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_personal_whisper_small_english_model","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_personal_whisper_small_english_model","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_personal_whisper_small_english_model| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/fractalego/personal-whisper-small.en-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_personal_whisper_small_english_model_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-19-asr_personal_whisper_small_english_model_pipeline_en.md new file mode 100644 index 00000000000000..c188644156cd69 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_personal_whisper_small_english_model_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_personal_whisper_small_english_model_pipeline pipeline WhisperForCTC from fractalego +author: John Snow Labs +name: asr_personal_whisper_small_english_model_pipeline +date: 2023-10-19 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_personal_whisper_small_english_model_pipeline` is a English model originally trained by fractalego. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_personal_whisper_small_english_model_pipeline_en_5.1.4_3.4_1697754518503.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_personal_whisper_small_english_model_pipeline_en_5.1.4_3.4_1697754518503.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_personal_whisper_small_english_model_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_personal_whisper_small_english_model_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_personal_whisper_small_english_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/fractalego/personal-whisper-small.en-model + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_lithuanian_finetune_lt.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_lithuanian_finetune_lt.md new file mode 100644 index 00000000000000..4d011976883339 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_lithuanian_finetune_lt.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Lithuanian asr_whisper_lithuanian_finetune WhisperForCTC from daniel-rdt +author: John Snow Labs +name: asr_whisper_lithuanian_finetune +date: 2023-10-19 +tags: [whisper, lt, open_source, asr, onnx] +task: Automatic Speech Recognition +language: lt +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_lithuanian_finetune` is a Lithuanian model originally trained by daniel-rdt. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_lithuanian_finetune_lt_5.1.4_3.4_1697755801160.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_lithuanian_finetune_lt_5.1.4_3.4_1697755801160.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_lithuanian_finetune","lt") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_lithuanian_finetune","lt") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_lithuanian_finetune| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|lt| +|Size:|1.7 GB| + +## References + +https://huggingface.co/daniel-rdt/whisper-lt-finetune \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_lithuanian_finetune_pipeline_lt.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_lithuanian_finetune_pipeline_lt.md new file mode 100644 index 00000000000000..203e29eaa84f11 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_lithuanian_finetune_pipeline_lt.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Lithuanian asr_whisper_lithuanian_finetune_pipeline pipeline WhisperForCTC from daniel-rdt +author: John Snow Labs +name: asr_whisper_lithuanian_finetune_pipeline +date: 2023-10-19 +tags: [whisper, lt, open_source, pipeline] +task: Automatic Speech Recognition +language: lt +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_lithuanian_finetune_pipeline` is a Lithuanian model originally trained by daniel-rdt. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_lithuanian_finetune_pipeline_lt_5.1.4_3.4_1697755826126.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_lithuanian_finetune_pipeline_lt_5.1.4_3.4_1697755826126.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_lithuanian_finetune_pipeline', lang = 'lt') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_lithuanian_finetune_pipeline', lang = 'lt') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_lithuanian_finetune_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|lt| +|Size:|1.7 GB| + +## References + +https://huggingface.co/daniel-rdt/whisper-lt-finetune + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_malayalam_first_model_ml.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_malayalam_first_model_ml.md new file mode 100644 index 00000000000000..a75c8818aa3776 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_malayalam_first_model_ml.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Malayalam asr_whisper_malayalam_first_model WhisperForCTC from kurianbenoy +author: John Snow Labs +name: asr_whisper_malayalam_first_model +date: 2023-10-19 +tags: [whisper, ml, open_source, asr, onnx] +task: Automatic Speech Recognition +language: ml +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_malayalam_first_model` is a Malayalam model originally trained by kurianbenoy. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_malayalam_first_model_ml_5.1.4_3.4_1697755379079.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_malayalam_first_model_ml_5.1.4_3.4_1697755379079.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_malayalam_first_model","ml") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_malayalam_first_model","ml") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_malayalam_first_model| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|ml| +|Size:|391.1 MB| + +## References + +https://huggingface.co/kurianbenoy/whisper-ml-first-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_malayalam_first_model_pipeline_ml.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_malayalam_first_model_pipeline_ml.md new file mode 100644 index 00000000000000..b698a24a4214b6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_malayalam_first_model_pipeline_ml.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Malayalam asr_whisper_malayalam_first_model_pipeline pipeline WhisperForCTC from kurianbenoy +author: John Snow Labs +name: asr_whisper_malayalam_first_model_pipeline +date: 2023-10-19 +tags: [whisper, ml, open_source, pipeline] +task: Automatic Speech Recognition +language: ml +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_malayalam_first_model_pipeline` is a Malayalam model originally trained by kurianbenoy. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_malayalam_first_model_pipeline_ml_5.1.4_3.4_1697755389149.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_malayalam_first_model_pipeline_ml_5.1.4_3.4_1697755389149.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_malayalam_first_model_pipeline', lang = 'ml') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_malayalam_first_model_pipeline', lang = 'ml') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_malayalam_first_model_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|ml| +|Size:|391.1 MB| + +## References + +https://huggingface.co/kurianbenoy/whisper-ml-first-model + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_bak_en.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_bak_en.md new file mode 100644 index 00000000000000..63a5a76517dd1b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_bak_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_small_bak WhisperForCTC from AigizK +author: John Snow Labs +name: asr_whisper_small_bak +date: 2023-10-19 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_bak` is a English model originally trained by AigizK. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_bak_en_5.1.4_3.4_1697753335079.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_bak_en_5.1.4_3.4_1697753335079.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_bak","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_bak","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_bak| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/AigizK/whisper-small-bak \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_bak_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_bak_pipeline_en.md new file mode 100644 index 00000000000000..16bed74424c586 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_bak_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_small_bak_pipeline pipeline WhisperForCTC from AigizK +author: John Snow Labs +name: asr_whisper_small_bak_pipeline +date: 2023-10-19 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_bak_pipeline` is a English model originally trained by AigizK. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_bak_pipeline_en_5.1.4_3.4_1697753365157.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_bak_pipeline_en_5.1.4_3.4_1697753365157.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_bak_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_bak_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_bak_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/AigizK/whisper-small-bak + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_bengali_subhadeep_en.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_bengali_subhadeep_en.md new file mode 100644 index 00000000000000..5d1382f034df6e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_bengali_subhadeep_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_small_bengali_subhadeep WhisperForCTC from Subhadeep +author: John Snow Labs +name: asr_whisper_small_bengali_subhadeep +date: 2023-10-19 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_bengali_subhadeep` is a English model originally trained by Subhadeep. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_bengali_subhadeep_en_5.1.4_3.4_1697757153165.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_bengali_subhadeep_en_5.1.4_3.4_1697757153165.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_bengali_subhadeep","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_bengali_subhadeep","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_bengali_subhadeep| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Subhadeep/whisper-small-bn \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_bengali_subhadeep_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_bengali_subhadeep_pipeline_en.md new file mode 100644 index 00000000000000..adcefbfeb3e49a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_bengali_subhadeep_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_small_bengali_subhadeep_pipeline pipeline WhisperForCTC from Subhadeep +author: John Snow Labs +name: asr_whisper_small_bengali_subhadeep_pipeline +date: 2023-10-19 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_bengali_subhadeep_pipeline` is a English model originally trained by Subhadeep. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_bengali_subhadeep_pipeline_en_5.1.4_3.4_1697757181862.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_bengali_subhadeep_pipeline_en_5.1.4_3.4_1697757181862.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_bengali_subhadeep_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_bengali_subhadeep_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_bengali_subhadeep_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Subhadeep/whisper-small-bn + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_chinese_tw_voidful_en.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_chinese_tw_voidful_en.md new file mode 100644 index 00000000000000..44deac6deb72fb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_chinese_tw_voidful_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_small_chinese_tw_voidful WhisperForCTC from voidful +author: John Snow Labs +name: asr_whisper_small_chinese_tw_voidful +date: 2023-10-19 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_chinese_tw_voidful` is a English model originally trained by voidful. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_chinese_tw_voidful_en_5.1.4_3.4_1697753255068.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_chinese_tw_voidful_en_5.1.4_3.4_1697753255068.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_chinese_tw_voidful","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_chinese_tw_voidful","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_chinese_tw_voidful| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/voidful/whisper-small-zh-TW \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_chinese_tw_voidful_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_chinese_tw_voidful_pipeline_en.md new file mode 100644 index 00000000000000..796c65d9089569 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_chinese_tw_voidful_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_small_chinese_tw_voidful_pipeline pipeline WhisperForCTC from voidful +author: John Snow Labs +name: asr_whisper_small_chinese_tw_voidful_pipeline +date: 2023-10-19 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_chinese_tw_voidful_pipeline` is a English model originally trained by voidful. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_chinese_tw_voidful_pipeline_en_5.1.4_3.4_1697753279228.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_chinese_tw_voidful_pipeline_en_5.1.4_3.4_1697753279228.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_chinese_tw_voidful_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_chinese_tw_voidful_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_chinese_tw_voidful_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/voidful/whisper-small-zh-TW + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_chinesebasetw_pipeline_zh.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_chinesebasetw_pipeline_zh.md new file mode 100644 index 00000000000000..5327aa27c093ed --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_chinesebasetw_pipeline_zh.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Chinese asr_whisper_small_chinesebasetw_pipeline pipeline WhisperForCTC from Jingmiao +author: John Snow Labs +name: asr_whisper_small_chinesebasetw_pipeline +date: 2023-10-19 +tags: [whisper, zh, open_source, pipeline] +task: Automatic Speech Recognition +language: zh +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_chinesebasetw_pipeline` is a Chinese model originally trained by Jingmiao. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_chinesebasetw_pipeline_zh_5.1.4_3.4_1697757472081.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_chinesebasetw_pipeline_zh_5.1.4_3.4_1697757472081.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_chinesebasetw_pipeline', lang = 'zh') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_chinesebasetw_pipeline', lang = 'zh') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_chinesebasetw_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|zh| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Jingmiao/whisper-small-chineseBaseTW + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_chinesebasetw_zh.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_chinesebasetw_zh.md new file mode 100644 index 00000000000000..530f36f0286351 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_chinesebasetw_zh.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Chinese asr_whisper_small_chinesebasetw WhisperForCTC from Jingmiao +author: John Snow Labs +name: asr_whisper_small_chinesebasetw +date: 2023-10-19 +tags: [whisper, zh, open_source, asr, onnx] +task: Automatic Speech Recognition +language: zh +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_chinesebasetw` is a Chinese model originally trained by Jingmiao. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_chinesebasetw_zh_5.1.4_3.4_1697757430683.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_chinesebasetw_zh_5.1.4_3.4_1697757430683.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_chinesebasetw","zh") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_chinesebasetw","zh") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_chinesebasetw| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|zh| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Jingmiao/whisper-small-chineseBaseTW \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_hindi_xinhuang_hi.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_hindi_xinhuang_hi.md new file mode 100644 index 00000000000000..3d80e7aa6073eb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_hindi_xinhuang_hi.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Hindi asr_whisper_small_hindi_xinhuang WhisperForCTC from xinhuang +author: John Snow Labs +name: asr_whisper_small_hindi_xinhuang +date: 2023-10-19 +tags: [whisper, hi, open_source, asr, onnx] +task: Automatic Speech Recognition +language: hi +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_hindi_xinhuang` is a Hindi model originally trained by xinhuang. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_hindi_xinhuang_hi_5.1.4_3.4_1697754908782.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_hindi_xinhuang_hi_5.1.4_3.4_1697754908782.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_hindi_xinhuang","hi") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_hindi_xinhuang","hi") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_hindi_xinhuang| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|hi| +|Size:|1.7 GB| + +## References + +https://huggingface.co/xinhuang/whisper-small-hi \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_hindi_xinhuang_pipeline_hi.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_hindi_xinhuang_pipeline_hi.md new file mode 100644 index 00000000000000..ece7023482e98c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_hindi_xinhuang_pipeline_hi.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Hindi asr_whisper_small_hindi_xinhuang_pipeline pipeline WhisperForCTC from xinhuang +author: John Snow Labs +name: asr_whisper_small_hindi_xinhuang_pipeline +date: 2023-10-19 +tags: [whisper, hi, open_source, pipeline] +task: Automatic Speech Recognition +language: hi +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_hindi_xinhuang_pipeline` is a Hindi model originally trained by xinhuang. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_hindi_xinhuang_pipeline_hi_5.1.4_3.4_1697754944761.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_hindi_xinhuang_pipeline_hi_5.1.4_3.4_1697754944761.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_hindi_xinhuang_pipeline', lang = 'hi') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_hindi_xinhuang_pipeline', lang = 'hi') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_hindi_xinhuang_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|hi| +|Size:|1.7 GB| + +## References + +https://huggingface.co/xinhuang/whisper-small-hi + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_lithuanian_deividasm_lt.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_lithuanian_deividasm_lt.md new file mode 100644 index 00000000000000..cc23fee11f736b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_lithuanian_deividasm_lt.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Lithuanian asr_whisper_small_lithuanian_deividasm WhisperForCTC from DeividasM +author: John Snow Labs +name: asr_whisper_small_lithuanian_deividasm +date: 2023-10-19 +tags: [whisper, lt, open_source, asr, onnx] +task: Automatic Speech Recognition +language: lt +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_lithuanian_deividasm` is a Lithuanian model originally trained by DeividasM. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_lithuanian_deividasm_lt_5.1.4_3.4_1697755670450.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_lithuanian_deividasm_lt_5.1.4_3.4_1697755670450.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_lithuanian_deividasm","lt") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_lithuanian_deividasm","lt") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_lithuanian_deividasm| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|lt| +|Size:|1.7 GB| + +## References + +https://huggingface.co/DeividasM/whisper-small-lt \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_lithuanian_deividasm_pipeline_lt.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_lithuanian_deividasm_pipeline_lt.md new file mode 100644 index 00000000000000..6540d1773e6067 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_lithuanian_deividasm_pipeline_lt.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Lithuanian asr_whisper_small_lithuanian_deividasm_pipeline pipeline WhisperForCTC from DeividasM +author: John Snow Labs +name: asr_whisper_small_lithuanian_deividasm_pipeline +date: 2023-10-19 +tags: [whisper, lt, open_source, pipeline] +task: Automatic Speech Recognition +language: lt +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_lithuanian_deividasm_pipeline` is a Lithuanian model originally trained by DeividasM. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_lithuanian_deividasm_pipeline_lt_5.1.4_3.4_1697755699167.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_lithuanian_deividasm_pipeline_lt_5.1.4_3.4_1697755699167.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_lithuanian_deividasm_pipeline', lang = 'lt') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_lithuanian_deividasm_pipeline', lang = 'lt') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_lithuanian_deividasm_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|lt| +|Size:|1.7 GB| + +## References + +https://huggingface.co/DeividasM/whisper-small-lt + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_nepali_np_ne.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_nepali_np_ne.md new file mode 100644 index 00000000000000..0a640afe7afa6c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_nepali_np_ne.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Nepali (macrolanguage) asr_whisper_small_nepali_np WhisperForCTC from julie200 +author: John Snow Labs +name: asr_whisper_small_nepali_np +date: 2023-10-19 +tags: [whisper, ne, open_source, asr, onnx] +task: Automatic Speech Recognition +language: ne +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_nepali_np` is a Nepali (macrolanguage) model originally trained by julie200. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_nepali_np_ne_5.1.4_3.4_1697758238849.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_nepali_np_ne_5.1.4_3.4_1697758238849.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_nepali_np","ne") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_nepali_np","ne") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_nepali_np| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|ne| +|Size:|1.7 GB| + +## References + +https://huggingface.co/julie200/whisper-small-ne-np \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_nepali_np_pipeline_ne.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_nepali_np_pipeline_ne.md new file mode 100644 index 00000000000000..12a86f64b2e774 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_nepali_np_pipeline_ne.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Nepali (macrolanguage) asr_whisper_small_nepali_np_pipeline pipeline WhisperForCTC from julie200 +author: John Snow Labs +name: asr_whisper_small_nepali_np_pipeline +date: 2023-10-19 +tags: [whisper, ne, open_source, pipeline] +task: Automatic Speech Recognition +language: ne +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_nepali_np_pipeline` is a Nepali (macrolanguage) model originally trained by julie200. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_nepali_np_pipeline_ne_5.1.4_3.4_1697758262511.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_nepali_np_pipeline_ne_5.1.4_3.4_1697758262511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_nepali_np_pipeline', lang = 'ne') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_nepali_np_pipeline', lang = 'ne') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_nepali_np_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|ne| +|Size:|1.7 GB| + +## References + +https://huggingface.co/julie200/whisper-small-ne-np + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_polish_aspik101_pipeline_pl.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_polish_aspik101_pipeline_pl.md new file mode 100644 index 00000000000000..21b32eed65c247 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_polish_aspik101_pipeline_pl.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Polish asr_whisper_small_polish_aspik101_pipeline pipeline WhisperForCTC from Aspik101 +author: John Snow Labs +name: asr_whisper_small_polish_aspik101_pipeline +date: 2023-10-19 +tags: [whisper, pl, open_source, pipeline] +task: Automatic Speech Recognition +language: pl +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_polish_aspik101_pipeline` is a Polish model originally trained by Aspik101. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_polish_aspik101_pipeline_pl_5.1.4_3.4_1697758839664.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_polish_aspik101_pipeline_pl_5.1.4_3.4_1697758839664.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_polish_aspik101_pipeline', lang = 'pl') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_polish_aspik101_pipeline', lang = 'pl') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_polish_aspik101_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|pl| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Aspik101/whisper-small-pl + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_polish_aspik101_pl.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_polish_aspik101_pl.md new file mode 100644 index 00000000000000..1a7bbfa6309da5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_polish_aspik101_pl.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Polish asr_whisper_small_polish_aspik101 WhisperForCTC from Aspik101 +author: John Snow Labs +name: asr_whisper_small_polish_aspik101 +date: 2023-10-19 +tags: [whisper, pl, open_source, asr, onnx] +task: Automatic Speech Recognition +language: pl +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_polish_aspik101` is a Polish model originally trained by Aspik101. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_polish_aspik101_pl_5.1.4_3.4_1697758808695.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_polish_aspik101_pl_5.1.4_3.4_1697758808695.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_polish_aspik101","pl") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_polish_aspik101","pl") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_polish_aspik101| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|pl| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Aspik101/whisper-small-pl \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_swedish_se_afroanton_en.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_swedish_se_afroanton_en.md new file mode 100644 index 00000000000000..2b4f360e9f8d84 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_swedish_se_afroanton_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_small_swedish_se_afroanton WhisperForCTC from afroanton +author: John Snow Labs +name: asr_whisper_small_swedish_se_afroanton +date: 2023-10-19 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_swedish_se_afroanton` is a English model originally trained by afroanton. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swedish_se_afroanton_en_5.1.4_3.4_1697758027499.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swedish_se_afroanton_en_5.1.4_3.4_1697758027499.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_swedish_se_afroanton","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_swedish_se_afroanton","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_swedish_se_afroanton| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/afroanton/whisper-small-sv-SE \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_swedish_se_afroanton_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_swedish_se_afroanton_pipeline_en.md new file mode 100644 index 00000000000000..fd3d60a6523db4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_swedish_se_afroanton_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_small_swedish_se_afroanton_pipeline pipeline WhisperForCTC from afroanton +author: John Snow Labs +name: asr_whisper_small_swedish_se_afroanton_pipeline +date: 2023-10-19 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_swedish_se_afroanton_pipeline` is a English model originally trained by afroanton. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swedish_se_afroanton_pipeline_en_5.1.4_3.4_1697758053063.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swedish_se_afroanton_pipeline_en_5.1.4_3.4_1697758053063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_swedish_se_afroanton_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_swedish_se_afroanton_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_swedish_se_afroanton_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/afroanton/whisper-small-sv-SE + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_swedish_test_3000_pipeline_sv.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_swedish_test_3000_pipeline_sv.md new file mode 100644 index 00000000000000..d6504ee55571ec --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_swedish_test_3000_pipeline_sv.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Swedish asr_whisper_small_swedish_test_3000_pipeline pipeline WhisperForCTC from ZinebSN +author: John Snow Labs +name: asr_whisper_small_swedish_test_3000_pipeline +date: 2023-10-19 +tags: [whisper, sv, open_source, pipeline] +task: Automatic Speech Recognition +language: sv +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_swedish_test_3000_pipeline` is a Swedish model originally trained by ZinebSN. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swedish_test_3000_pipeline_sv_5.1.4_3.4_1697754957297.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swedish_test_3000_pipeline_sv_5.1.4_3.4_1697754957297.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_swedish_test_3000_pipeline', lang = 'sv') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_swedish_test_3000_pipeline', lang = 'sv') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_swedish_test_3000_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|sv| +|Size:|1.7 GB| + +## References + +https://huggingface.co/ZinebSN/whisper-small-swedish-Test-3000 + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_swedish_test_3000_sv.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_swedish_test_3000_sv.md new file mode 100644 index 00000000000000..d0496b955ce397 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_swedish_test_3000_sv.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Swedish asr_whisper_small_swedish_test_3000 WhisperForCTC from ZinebSN +author: John Snow Labs +name: asr_whisper_small_swedish_test_3000 +date: 2023-10-19 +tags: [whisper, sv, open_source, asr, onnx] +task: Automatic Speech Recognition +language: sv +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_swedish_test_3000` is a Swedish model originally trained by ZinebSN. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swedish_test_3000_sv_5.1.4_3.4_1697754925389.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swedish_test_3000_sv_5.1.4_3.4_1697754925389.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_swedish_test_3000","sv") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_swedish_test_3000","sv") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_swedish_test_3000| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|sv| +|Size:|1.7 GB| + +## References + +https://huggingface.co/ZinebSN/whisper-small-swedish-Test-3000 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic_en.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic_en.md new file mode 100644 index 00000000000000..5fb84b16c4ff62 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic WhisperForCTC from kpriyanshu256 +author: John Snow Labs +name: asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic +date: 2023-10-19 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic` is a English model originally trained by kpriyanshu256. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic_en_5.1.4_3.4_1697754395649.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic_en_5.1.4_3.4_1697754395649.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/kpriyanshu256/whisper-small-ur-1000-64-1e-05-pretrain-ar \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic_pipeline_en.md new file mode 100644 index 00000000000000..7bc5bc3d8f8794 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic_pipeline pipeline WhisperForCTC from kpriyanshu256 +author: John Snow Labs +name: asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic_pipeline +date: 2023-10-19 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic_pipeline` is a English model originally trained by kpriyanshu256. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic_pipeline_en_5.1.4_3.4_1697754437394.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic_pipeline_en_5.1.4_3.4_1697754437394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_urdu_1000_64_1e_05_pretrain_arabic_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/kpriyanshu256/whisper-small-ur-1000-64-1e-05-pretrain-ar + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_uzbek_pipeline_uz.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_uzbek_pipeline_uz.md new file mode 100644 index 00000000000000..cabf8598ecdb34 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_uzbek_pipeline_uz.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Uzbek asr_whisper_small_uzbek_pipeline pipeline WhisperForCTC from BlueRaccoon +author: John Snow Labs +name: asr_whisper_small_uzbek_pipeline +date: 2023-10-19 +tags: [whisper, uz, open_source, pipeline] +task: Automatic Speech Recognition +language: uz +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_uzbek_pipeline` is a Uzbek model originally trained by BlueRaccoon. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_uzbek_pipeline_uz_5.1.4_3.4_1697758115932.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_uzbek_pipeline_uz_5.1.4_3.4_1697758115932.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_uzbek_pipeline', lang = 'uz') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_uzbek_pipeline', lang = 'uz') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_uzbek_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|uz| +|Size:|1.7 GB| + +## References + +https://huggingface.co/BlueRaccoon/whisper-small-uz + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_uzbek_uz.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_uzbek_uz.md new file mode 100644 index 00000000000000..63146e9307e81d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_small_uzbek_uz.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Uzbek asr_whisper_small_uzbek WhisperForCTC from BlueRaccoon +author: John Snow Labs +name: asr_whisper_small_uzbek +date: 2023-10-19 +tags: [whisper, uz, open_source, asr, onnx] +task: Automatic Speech Recognition +language: uz +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_uzbek` is a Uzbek model originally trained by BlueRaccoon. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_uzbek_uz_5.1.4_3.4_1697758091527.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_uzbek_uz_5.1.4_3.4_1697758091527.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_uzbek","uz") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_uzbek","uz") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_uzbek| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|uz| +|Size:|1.7 GB| + +## References + +https://huggingface.co/BlueRaccoon/whisper-small-uz \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_tiny_polish_pipeline_pl.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_tiny_polish_pipeline_pl.md new file mode 100644 index 00000000000000..a82842463d19c6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_tiny_polish_pipeline_pl.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Polish asr_whisper_tiny_polish_pipeline pipeline WhisperForCTC from Aspik101 +author: John Snow Labs +name: asr_whisper_tiny_polish_pipeline +date: 2023-10-19 +tags: [whisper, pl, open_source, pipeline] +task: Automatic Speech Recognition +language: pl +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_polish_pipeline` is a Polish model originally trained by Aspik101. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_polish_pipeline_pl_5.1.4_3.4_1697759156199.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_polish_pipeline_pl_5.1.4_3.4_1697759156199.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_tiny_polish_pipeline', lang = 'pl') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_tiny_polish_pipeline', lang = 'pl') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_polish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|pl| +|Size:|390.7 MB| + +## References + +https://huggingface.co/Aspik101/whisper-tiny-pl + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_tiny_polish_pl.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_tiny_polish_pl.md new file mode 100644 index 00000000000000..20eb9a7e90fa34 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_tiny_polish_pl.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Polish asr_whisper_tiny_polish WhisperForCTC from Aspik101 +author: John Snow Labs +name: asr_whisper_tiny_polish +date: 2023-10-19 +tags: [whisper, pl, open_source, asr, onnx] +task: Automatic Speech Recognition +language: pl +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_polish` is a Polish model originally trained by Aspik101. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_polish_pl_5.1.4_3.4_1697759148948.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_polish_pl_5.1.4_3.4_1697759148948.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_polish","pl") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_polish","pl") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_polish| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|pl| +|Size:|390.7 MB| + +## References + +https://huggingface.co/Aspik101/whisper-tiny-pl \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_tiny_tamil_example_pipeline_ta.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_tiny_tamil_example_pipeline_ta.md new file mode 100644 index 00000000000000..24f1515ee7e316 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_tiny_tamil_example_pipeline_ta.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Tamil asr_whisper_tiny_tamil_example_pipeline pipeline WhisperForCTC from parambharat +author: John Snow Labs +name: asr_whisper_tiny_tamil_example_pipeline +date: 2023-10-19 +tags: [whisper, ta, open_source, pipeline] +task: Automatic Speech Recognition +language: ta +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_tamil_example_pipeline` is a Tamil model originally trained by parambharat. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_tamil_example_pipeline_ta_5.1.4_3.4_1697754897889.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_tamil_example_pipeline_ta_5.1.4_3.4_1697754897889.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_tiny_tamil_example_pipeline', lang = 'ta') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_tiny_tamil_example_pipeline', lang = 'ta') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_tamil_example_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|ta| +|Size:|390.9 MB| + +## References + +https://huggingface.co/parambharat/whisper-tiny-ta-example + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_tiny_tamil_example_ta.md b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_tiny_tamil_example_ta.md new file mode 100644 index 00000000000000..40505bb5ea47de --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-19-asr_whisper_tiny_tamil_example_ta.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Tamil asr_whisper_tiny_tamil_example WhisperForCTC from parambharat +author: John Snow Labs +name: asr_whisper_tiny_tamil_example +date: 2023-10-19 +tags: [whisper, ta, open_source, asr, onnx] +task: Automatic Speech Recognition +language: ta +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_tamil_example` is a Tamil model originally trained by parambharat. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_tamil_example_ta_5.1.4_3.4_1697754888104.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_tamil_example_ta_5.1.4_3.4_1697754888104.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_tamil_example","ta") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_tamil_example","ta") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_tamil_example| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|ta| +|Size:|390.9 MB| + +## References + +https://huggingface.co/parambharat/whisper-tiny-ta-example \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_base_swedish_en.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_base_swedish_en.md new file mode 100644 index 00000000000000..e5374a6b02df8d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_base_swedish_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_base_swedish WhisperForCTC from rscolati +author: John Snow Labs +name: asr_whisper_base_swedish +date: 2023-10-20 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_base_swedish` is a English model originally trained by rscolati. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_base_swedish_en_5.1.4_3.4_1697761530317.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_base_swedish_en_5.1.4_3.4_1697761530317.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_base_swedish","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_base_swedish","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_base_swedish| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|643.4 MB| + +## References + +https://huggingface.co/rscolati/whisper-base-sv \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_base_swedish_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_base_swedish_pipeline_en.md new file mode 100644 index 00000000000000..6698bf87195e1d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_base_swedish_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_base_swedish_pipeline pipeline WhisperForCTC from rscolati +author: John Snow Labs +name: asr_whisper_base_swedish_pipeline +date: 2023-10-20 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_base_swedish_pipeline` is a English model originally trained by rscolati. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_base_swedish_pipeline_en_5.1.4_3.4_1697761542899.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_base_swedish_pipeline_en_5.1.4_3.4_1697761542899.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_base_swedish_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_base_swedish_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_base_swedish_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|643.4 MB| + +## References + +https://huggingface.co/rscolati/whisper-base-sv + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_danish_small_augmented_da.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_danish_small_augmented_da.md new file mode 100644 index 00000000000000..738c57acff5b1c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_danish_small_augmented_da.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Danish asr_whisper_danish_small_augmented WhisperForCTC from ALM +author: John Snow Labs +name: asr_whisper_danish_small_augmented +date: 2023-10-20 +tags: [whisper, da, open_source, asr, onnx] +task: Automatic Speech Recognition +language: da +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_danish_small_augmented` is a Danish model originally trained by ALM. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_danish_small_augmented_da_5.1.4_3.4_1697768052248.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_danish_small_augmented_da_5.1.4_3.4_1697768052248.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_danish_small_augmented","da") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_danish_small_augmented","da") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_danish_small_augmented| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|da| +|Size:|1.7 GB| + +## References + +https://huggingface.co/ALM/whisper-da-small-augmented \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_danish_small_augmented_pipeline_da.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_danish_small_augmented_pipeline_da.md new file mode 100644 index 00000000000000..80706f147bbcd6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_danish_small_augmented_pipeline_da.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Danish asr_whisper_danish_small_augmented_pipeline pipeline WhisperForCTC from ALM +author: John Snow Labs +name: asr_whisper_danish_small_augmented_pipeline +date: 2023-10-20 +tags: [whisper, da, open_source, pipeline] +task: Automatic Speech Recognition +language: da +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_danish_small_augmented_pipeline` is a Danish model originally trained by ALM. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_danish_small_augmented_pipeline_da_5.1.4_3.4_1697768078968.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_danish_small_augmented_pipeline_da_5.1.4_3.4_1697768078968.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_danish_small_augmented_pipeline', lang = 'da') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_danish_small_augmented_pipeline', lang = 'da') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_danish_small_augmented_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|da| +|Size:|1.7 GB| + +## References + +https://huggingface.co/ALM/whisper-da-small-augmented + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_arabic_cv11_en.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_arabic_cv11_en.md new file mode 100644 index 00000000000000..97d1cee82f35fb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_arabic_cv11_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_small_arabic_cv11 WhisperForCTC from hkhdair +author: John Snow Labs +name: asr_whisper_small_arabic_cv11 +date: 2023-10-20 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_arabic_cv11` is a English model originally trained by hkhdair. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_arabic_cv11_en_5.1.4_3.4_1697764506687.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_arabic_cv11_en_5.1.4_3.4_1697764506687.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_arabic_cv11","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_arabic_cv11","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_arabic_cv11| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/hkhdair/whisper-small-ar-cv11 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_arabic_cv11_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_arabic_cv11_pipeline_en.md new file mode 100644 index 00000000000000..24ae96a1db563c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_arabic_cv11_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_small_arabic_cv11_pipeline pipeline WhisperForCTC from hkhdair +author: John Snow Labs +name: asr_whisper_small_arabic_cv11_pipeline +date: 2023-10-20 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_arabic_cv11_pipeline` is a English model originally trained by hkhdair. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_arabic_cv11_pipeline_en_5.1.4_3.4_1697764533389.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_arabic_cv11_pipeline_en_5.1.4_3.4_1697764533389.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_arabic_cv11_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_arabic_cv11_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_arabic_cv11_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/hkhdair/whisper-small-ar-cv11 + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_armenian_hy.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_armenian_hy.md new file mode 100644 index 00000000000000..64ca52425b8f33 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_armenian_hy.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Armenian asr_whisper_small_armenian WhisperForCTC from pranay-j +author: John Snow Labs +name: asr_whisper_small_armenian +date: 2023-10-20 +tags: [whisper, hy, open_source, asr, onnx] +task: Automatic Speech Recognition +language: hy +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_armenian` is a Armenian model originally trained by pranay-j. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_armenian_hy_5.1.4_3.4_1697760551180.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_armenian_hy_5.1.4_3.4_1697760551180.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_armenian","hy") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_armenian","hy") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_armenian| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|hy| +|Size:|1.7 GB| + +## References + +https://huggingface.co/pranay-j/whisper-small-hy \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_armenian_pipeline_hy.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_armenian_pipeline_hy.md new file mode 100644 index 00000000000000..61ccef878b4b7e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_armenian_pipeline_hy.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Armenian asr_whisper_small_armenian_pipeline pipeline WhisperForCTC from pranay-j +author: John Snow Labs +name: asr_whisper_small_armenian_pipeline +date: 2023-10-20 +tags: [whisper, hy, open_source, pipeline] +task: Automatic Speech Recognition +language: hy +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_armenian_pipeline` is a Armenian model originally trained by pranay-j. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_armenian_pipeline_hy_5.1.4_3.4_1697760577067.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_armenian_pipeline_hy_5.1.4_3.4_1697760577067.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_armenian_pipeline', lang = 'hy') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_armenian_pipeline', lang = 'hy') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_armenian_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|hy| +|Size:|1.7 GB| + +## References + +https://huggingface.co/pranay-j/whisper-small-hy + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_dutch_nl.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_dutch_nl.md new file mode 100644 index 00000000000000..a92fa297b5c127 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_dutch_nl.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Dutch, Flemish asr_whisper_small_dutch WhisperForCTC from pplantinga +author: John Snow Labs +name: asr_whisper_small_dutch +date: 2023-10-20 +tags: [whisper, nl, open_source, asr, onnx] +task: Automatic Speech Recognition +language: nl +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_dutch` is a Dutch, Flemish model originally trained by pplantinga. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_dutch_nl_5.1.4_3.4_1697760208052.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_dutch_nl_5.1.4_3.4_1697760208052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_dutch","nl") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_dutch","nl") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_dutch| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|nl| +|Size:|1.7 GB| + +## References + +https://huggingface.co/pplantinga/whisper-small-nl \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_dutch_pipeline_nl.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_dutch_pipeline_nl.md new file mode 100644 index 00000000000000..40d28e76f0830d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_dutch_pipeline_nl.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Dutch, Flemish asr_whisper_small_dutch_pipeline pipeline WhisperForCTC from pplantinga +author: John Snow Labs +name: asr_whisper_small_dutch_pipeline +date: 2023-10-20 +tags: [whisper, nl, open_source, pipeline] +task: Automatic Speech Recognition +language: nl +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_dutch_pipeline` is a Dutch, Flemish model originally trained by pplantinga. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_dutch_pipeline_nl_5.1.4_3.4_1697760252058.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_dutch_pipeline_nl_5.1.4_3.4_1697760252058.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_dutch_pipeline', lang = 'nl') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_dutch_pipeline', lang = 'nl') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_dutch_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|nl| +|Size:|1.7 GB| + +## References + +https://huggingface.co/pplantinga/whisper-small-nl + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_english_blueraccoon_en.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_english_blueraccoon_en.md new file mode 100644 index 00000000000000..7dcaca2456739f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_english_blueraccoon_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_small_english_blueraccoon WhisperForCTC from BlueRaccoon +author: John Snow Labs +name: asr_whisper_small_english_blueraccoon +date: 2023-10-20 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_english_blueraccoon` is a English model originally trained by BlueRaccoon. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_english_blueraccoon_en_5.1.4_3.4_1697760099807.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_english_blueraccoon_en_5.1.4_3.4_1697760099807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_english_blueraccoon","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_english_blueraccoon","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_english_blueraccoon| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/BlueRaccoon/whisper-small-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_english_blueraccoon_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_english_blueraccoon_pipeline_en.md new file mode 100644 index 00000000000000..7011d52e86a2fe --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_english_blueraccoon_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_small_english_blueraccoon_pipeline pipeline WhisperForCTC from BlueRaccoon +author: John Snow Labs +name: asr_whisper_small_english_blueraccoon_pipeline +date: 2023-10-20 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_english_blueraccoon_pipeline` is a English model originally trained by BlueRaccoon. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_english_blueraccoon_pipeline_en_5.1.4_3.4_1697760125385.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_english_blueraccoon_pipeline_en_5.1.4_3.4_1697760125385.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_english_blueraccoon_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_english_blueraccoon_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_english_blueraccoon_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/BlueRaccoon/whisper-small-en + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_finnish_sgangireddy_fi.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_finnish_sgangireddy_fi.md new file mode 100644 index 00000000000000..1e4566602d64ef --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_finnish_sgangireddy_fi.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Finnish asr_whisper_small_finnish_sgangireddy WhisperForCTC from sgangireddy +author: John Snow Labs +name: asr_whisper_small_finnish_sgangireddy +date: 2023-10-20 +tags: [whisper, fi, open_source, asr, onnx] +task: Automatic Speech Recognition +language: fi +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_finnish_sgangireddy` is a Finnish model originally trained by sgangireddy. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_finnish_sgangireddy_fi_5.1.4_3.4_1697760961669.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_finnish_sgangireddy_fi_5.1.4_3.4_1697760961669.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_finnish_sgangireddy","fi") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_finnish_sgangireddy","fi") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_finnish_sgangireddy| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|fi| +|Size:|1.7 GB| + +## References + +https://huggingface.co/sgangireddy/whisper-small-fi \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_finnish_sgangireddy_pipeline_fi.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_finnish_sgangireddy_pipeline_fi.md new file mode 100644 index 00000000000000..88e37bc7b7970a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_finnish_sgangireddy_pipeline_fi.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Finnish asr_whisper_small_finnish_sgangireddy_pipeline pipeline WhisperForCTC from sgangireddy +author: John Snow Labs +name: asr_whisper_small_finnish_sgangireddy_pipeline +date: 2023-10-20 +tags: [whisper, fi, open_source, pipeline] +task: Automatic Speech Recognition +language: fi +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_finnish_sgangireddy_pipeline` is a Finnish model originally trained by sgangireddy. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_finnish_sgangireddy_pipeline_fi_5.1.4_3.4_1697760986850.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_finnish_sgangireddy_pipeline_fi_5.1.4_3.4_1697760986850.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_finnish_sgangireddy_pipeline', lang = 'fi') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_finnish_sgangireddy_pipeline', lang = 'fi') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_finnish_sgangireddy_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|fi| +|Size:|1.7 GB| + +## References + +https://huggingface.co/sgangireddy/whisper-small-fi + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_french_yocel1_hi.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_french_yocel1_hi.md new file mode 100644 index 00000000000000..480878cee41c94 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_french_yocel1_hi.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Hindi asr_whisper_small_french_yocel1 WhisperForCTC from Yocel1 +author: John Snow Labs +name: asr_whisper_small_french_yocel1 +date: 2023-10-20 +tags: [whisper, hi, open_source, asr, onnx] +task: Automatic Speech Recognition +language: hi +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_french_yocel1` is a Hindi model originally trained by Yocel1. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_french_yocel1_hi_5.1.4_3.4_1697762514859.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_french_yocel1_hi_5.1.4_3.4_1697762514859.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_french_yocel1","hi") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_french_yocel1","hi") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_french_yocel1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|hi| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Yocel1/whisper-small-fr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_french_yocel1_pipeline_hi.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_french_yocel1_pipeline_hi.md new file mode 100644 index 00000000000000..33958cc8436431 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_french_yocel1_pipeline_hi.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Hindi asr_whisper_small_french_yocel1_pipeline pipeline WhisperForCTC from Yocel1 +author: John Snow Labs +name: asr_whisper_small_french_yocel1_pipeline +date: 2023-10-20 +tags: [whisper, hi, open_source, pipeline] +task: Automatic Speech Recognition +language: hi +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_french_yocel1_pipeline` is a Hindi model originally trained by Yocel1. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_french_yocel1_pipeline_hi_5.1.4_3.4_1697762545502.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_french_yocel1_pipeline_hi_5.1.4_3.4_1697762545502.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_french_yocel1_pipeline', lang = 'hi') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_french_yocel1_pipeline', lang = 'hi') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_french_yocel1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|hi| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Yocel1/whisper-small-fr + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_hungarian_cv11_en.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_hungarian_cv11_en.md new file mode 100644 index 00000000000000..5447154ab9eb55 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_hungarian_cv11_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_small_hungarian_cv11 WhisperForCTC from mikr +author: John Snow Labs +name: asr_whisper_small_hungarian_cv11 +date: 2023-10-20 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_hungarian_cv11` is a English model originally trained by mikr. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_hungarian_cv11_en_5.1.4_3.4_1697762655252.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_hungarian_cv11_en_5.1.4_3.4_1697762655252.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_hungarian_cv11","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_hungarian_cv11","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_hungarian_cv11| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/mikr/whisper-small-hu-cv11 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_hungarian_cv11_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_hungarian_cv11_pipeline_en.md new file mode 100644 index 00000000000000..5168ebf5cbf736 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_hungarian_cv11_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_small_hungarian_cv11_pipeline pipeline WhisperForCTC from mikr +author: John Snow Labs +name: asr_whisper_small_hungarian_cv11_pipeline +date: 2023-10-20 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_hungarian_cv11_pipeline` is a English model originally trained by mikr. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_hungarian_cv11_pipeline_en_5.1.4_3.4_1697762679177.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_hungarian_cv11_pipeline_en_5.1.4_3.4_1697762679177.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_hungarian_cv11_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_hungarian_cv11_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_hungarian_cv11_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/mikr/whisper-small-hu-cv11 + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_japanese_vumichien_ja.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_japanese_vumichien_ja.md new file mode 100644 index 00000000000000..2fd53e69bf0775 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_japanese_vumichien_ja.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Japanese asr_whisper_small_japanese_vumichien WhisperForCTC from vumichien +author: John Snow Labs +name: asr_whisper_small_japanese_vumichien +date: 2023-10-20 +tags: [whisper, ja, open_source, asr, onnx] +task: Automatic Speech Recognition +language: ja +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_japanese_vumichien` is a Japanese model originally trained by vumichien. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_japanese_vumichien_ja_5.1.4_3.4_1697766130278.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_japanese_vumichien_ja_5.1.4_3.4_1697766130278.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_japanese_vumichien","ja") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_japanese_vumichien","ja") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_japanese_vumichien| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|ja| +|Size:|1.7 GB| + +## References + +https://huggingface.co/vumichien/whisper-small-ja \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_japanese_vumichien_pipeline_ja.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_japanese_vumichien_pipeline_ja.md new file mode 100644 index 00000000000000..9292bb7027ebac --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_japanese_vumichien_pipeline_ja.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Japanese asr_whisper_small_japanese_vumichien_pipeline pipeline WhisperForCTC from vumichien +author: John Snow Labs +name: asr_whisper_small_japanese_vumichien_pipeline +date: 2023-10-20 +tags: [whisper, ja, open_source, pipeline] +task: Automatic Speech Recognition +language: ja +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_japanese_vumichien_pipeline` is a Japanese model originally trained by vumichien. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_japanese_vumichien_pipeline_ja_5.1.4_3.4_1697766170978.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_japanese_vumichien_pipeline_ja_5.1.4_3.4_1697766170978.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_japanese_vumichien_pipeline', lang = 'ja') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_japanese_vumichien_pipeline', lang = 'ja') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_japanese_vumichien_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|ja| +|Size:|1.7 GB| + +## References + +https://huggingface.co/vumichien/whisper-small-ja + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_korean_fl_ko.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_korean_fl_ko.md new file mode 100644 index 00000000000000..cbaf1e05b2e1d7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_korean_fl_ko.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Korean asr_whisper_small_korean_fl WhisperForCTC from p4b +author: John Snow Labs +name: asr_whisper_small_korean_fl +date: 2023-10-20 +tags: [whisper, ko, open_source, asr, onnx] +task: Automatic Speech Recognition +language: ko +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_korean_fl` is a Korean model originally trained by p4b. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_korean_fl_ko_5.1.4_3.4_1697768363999.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_korean_fl_ko_5.1.4_3.4_1697768363999.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_korean_fl","ko") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_korean_fl","ko") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_korean_fl| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|ko| +|Size:|1.1 GB| + +## References + +https://huggingface.co/p4b/whisper-small-ko-fl \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_korean_fl_pipeline_ko.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_korean_fl_pipeline_ko.md new file mode 100644 index 00000000000000..3dbfd83f0d2540 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_korean_fl_pipeline_ko.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Korean asr_whisper_small_korean_fl_pipeline pipeline WhisperForCTC from p4b +author: John Snow Labs +name: asr_whisper_small_korean_fl_pipeline +date: 2023-10-20 +tags: [whisper, ko, open_source, pipeline] +task: Automatic Speech Recognition +language: ko +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_korean_fl_pipeline` is a Korean model originally trained by p4b. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_korean_fl_pipeline_ko_5.1.4_3.4_1697768403117.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_korean_fl_pipeline_ko_5.1.4_3.4_1697768403117.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_korean_fl_pipeline', lang = 'ko') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_korean_fl_pipeline', lang = 'ko') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_korean_fl_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|ko| +|Size:|1.1 GB| + +## References + +https://huggingface.co/p4b/whisper-small-ko-fl + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_lithuanian_serbian_v2_en.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_lithuanian_serbian_v2_en.md new file mode 100644 index 00000000000000..e9068f9f5feae0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_lithuanian_serbian_v2_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_small_lithuanian_serbian_v2 WhisperForCTC from jraramhoej +author: John Snow Labs +name: asr_whisper_small_lithuanian_serbian_v2 +date: 2023-10-20 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_lithuanian_serbian_v2` is a English model originally trained by jraramhoej. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_lithuanian_serbian_v2_en_5.1.4_3.4_1697761536370.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_lithuanian_serbian_v2_en_5.1.4_3.4_1697761536370.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_lithuanian_serbian_v2","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_lithuanian_serbian_v2","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_lithuanian_serbian_v2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/jraramhoej/whisper-small-lt-sr-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_lithuanian_serbian_v2_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_lithuanian_serbian_v2_pipeline_en.md new file mode 100644 index 00000000000000..8e4bb662490fa7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_lithuanian_serbian_v2_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_small_lithuanian_serbian_v2_pipeline pipeline WhisperForCTC from jraramhoej +author: John Snow Labs +name: asr_whisper_small_lithuanian_serbian_v2_pipeline +date: 2023-10-20 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_lithuanian_serbian_v2_pipeline` is a English model originally trained by jraramhoej. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_lithuanian_serbian_v2_pipeline_en_5.1.4_3.4_1697761572103.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_lithuanian_serbian_v2_pipeline_en_5.1.4_3.4_1697761572103.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_lithuanian_serbian_v2_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_lithuanian_serbian_v2_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_lithuanian_serbian_v2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/jraramhoej/whisper-small-lt-sr-v2 + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_mongolian_3_en.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_mongolian_3_en.md new file mode 100644 index 00000000000000..5eac73456783ec --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_mongolian_3_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_small_mongolian_3 WhisperForCTC from bayartsogt +author: John Snow Labs +name: asr_whisper_small_mongolian_3 +date: 2023-10-20 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_mongolian_3` is a English model originally trained by bayartsogt. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_mongolian_3_en_5.1.4_3.4_1697766978958.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_mongolian_3_en_5.1.4_3.4_1697766978958.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_mongolian_3","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_mongolian_3","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_mongolian_3| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/bayartsogt/whisper-small-mn-3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_mongolian_3_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_mongolian_3_pipeline_en.md new file mode 100644 index 00000000000000..bddb3b05420fb3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_mongolian_3_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_small_mongolian_3_pipeline pipeline WhisperForCTC from bayartsogt +author: John Snow Labs +name: asr_whisper_small_mongolian_3_pipeline +date: 2023-10-20 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_mongolian_3_pipeline` is a English model originally trained by bayartsogt. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_mongolian_3_pipeline_en_5.1.4_3.4_1697767005814.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_mongolian_3_pipeline_en_5.1.4_3.4_1697767005814.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_mongolian_3_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_mongolian_3_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_mongolian_3_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/bayartsogt/whisper-small-mn-3 + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_nob_no.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_nob_no.md new file mode 100644 index 00000000000000..6d0612f568f918 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_nob_no.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Norwegian asr_whisper_small_nob WhisperForCTC from NbAiLab +author: John Snow Labs +name: asr_whisper_small_nob +date: 2023-10-20 +tags: [whisper, "no", open_source, asr, onnx] +task: Automatic Speech Recognition +language: "no" +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_nob` is a Norwegian model originally trained by NbAiLab. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_nob_no_5.1.4_3.4_1697767866471.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_nob_no_5.1.4_3.4_1697767866471.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_nob","no") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_nob","no") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_nob| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|no| +|Size:|1.1 GB| + +## References + +https://huggingface.co/NbAiLab/whisper-small-nob \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_nob_pipeline_no.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_nob_pipeline_no.md new file mode 100644 index 00000000000000..1e5e58697367e6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_nob_pipeline_no.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Norwegian asr_whisper_small_nob_pipeline pipeline WhisperForCTC from NbAiLab +author: John Snow Labs +name: asr_whisper_small_nob_pipeline +date: 2023-10-20 +tags: [whisper, "no", open_source, pipeline] +task: Automatic Speech Recognition +language: "no" +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_nob_pipeline` is a Norwegian model originally trained by NbAiLab. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_nob_pipeline_no_5.1.4_3.4_1697767890596.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_nob_pipeline_no_5.1.4_3.4_1697767890596.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_nob_pipeline', lang = 'no') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_nob_pipeline', lang = 'no') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_nob_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|no| +|Size:|1.1 GB| + +## References + +https://huggingface.co/NbAiLab/whisper-small-nob + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_pashto_ihanif_pipeline_ps.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_pashto_ihanif_pipeline_ps.md new file mode 100644 index 00000000000000..35b47d9c30cf50 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_pashto_ihanif_pipeline_ps.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Pashto, Pushto asr_whisper_small_pashto_ihanif_pipeline pipeline WhisperForCTC from ihanif +author: John Snow Labs +name: asr_whisper_small_pashto_ihanif_pipeline +date: 2023-10-20 +tags: [whisper, ps, open_source, pipeline] +task: Automatic Speech Recognition +language: ps +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_pashto_ihanif_pipeline` is a Pashto, Pushto model originally trained by ihanif. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_pashto_ihanif_pipeline_ps_5.1.4_3.4_1697764646764.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_pashto_ihanif_pipeline_ps_5.1.4_3.4_1697764646764.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_pashto_ihanif_pipeline', lang = 'ps') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_pashto_ihanif_pipeline', lang = 'ps') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_pashto_ihanif_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|ps| +|Size:|1.7 GB| + +## References + +https://huggingface.co/ihanif/whisper-small-pashto + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_pashto_ihanif_ps.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_pashto_ihanif_ps.md new file mode 100644 index 00000000000000..c88d37d77d2e84 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_pashto_ihanif_ps.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Pashto, Pushto asr_whisper_small_pashto_ihanif WhisperForCTC from ihanif +author: John Snow Labs +name: asr_whisper_small_pashto_ihanif +date: 2023-10-20 +tags: [whisper, ps, open_source, asr, onnx] +task: Automatic Speech Recognition +language: ps +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_pashto_ihanif` is a Pashto, Pushto model originally trained by ihanif. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_pashto_ihanif_ps_5.1.4_3.4_1697764620611.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_pashto_ihanif_ps_5.1.4_3.4_1697764620611.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_pashto_ihanif","ps") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_pashto_ihanif","ps") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_pashto_ihanif| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|ps| +|Size:|1.7 GB| + +## References + +https://huggingface.co/ihanif/whisper-small-pashto \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_punjabi_eastern_pa.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_punjabi_eastern_pa.md new file mode 100644 index 00000000000000..a1ec98043e0395 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_punjabi_eastern_pa.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Panjabi, Punjabi asr_whisper_small_punjabi_eastern WhisperForCTC from anuragshas +author: John Snow Labs +name: asr_whisper_small_punjabi_eastern +date: 2023-10-20 +tags: [whisper, pa, open_source, asr, onnx] +task: Automatic Speech Recognition +language: pa +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_punjabi_eastern` is a Panjabi, Punjabi model originally trained by anuragshas. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_punjabi_eastern_pa_5.1.4_3.4_1697796901247.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_punjabi_eastern_pa_5.1.4_3.4_1697796901247.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_punjabi_eastern","pa") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_punjabi_eastern","pa") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_punjabi_eastern| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|pa| +|Size:|1.7 GB| + +## References + +https://huggingface.co/anuragshas/whisper-small-pa \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_punjabi_eastern_pipeline_pa.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_punjabi_eastern_pipeline_pa.md new file mode 100644 index 00000000000000..5a99a1a34d1836 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_punjabi_eastern_pipeline_pa.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Panjabi, Punjabi asr_whisper_small_punjabi_eastern_pipeline pipeline WhisperForCTC from anuragshas +author: John Snow Labs +name: asr_whisper_small_punjabi_eastern_pipeline +date: 2023-10-20 +tags: [whisper, pa, open_source, pipeline] +task: Automatic Speech Recognition +language: pa +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_punjabi_eastern_pipeline` is a Panjabi, Punjabi model originally trained by anuragshas. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_punjabi_eastern_pipeline_pa_5.1.4_3.4_1697796972727.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_punjabi_eastern_pipeline_pa_5.1.4_3.4_1697796972727.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_punjabi_eastern_pipeline', lang = 'pa') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_punjabi_eastern_pipeline', lang = 'pa') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_punjabi_eastern_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|pa| +|Size:|1.7 GB| + +## References + +https://huggingface.co/anuragshas/whisper-small-pa + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_spanish_1e_6_en.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_spanish_1e_6_en.md new file mode 100644 index 00000000000000..7d4c2498c493c1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_spanish_1e_6_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_small_spanish_1e_6 WhisperForCTC from sanchit-gandhi +author: John Snow Labs +name: asr_whisper_small_spanish_1e_6 +date: 2023-10-20 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_spanish_1e_6` is a English model originally trained by sanchit-gandhi. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_spanish_1e_6_en_5.1.4_3.4_1697760169069.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_spanish_1e_6_en_5.1.4_3.4_1697760169069.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_spanish_1e_6","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_spanish_1e_6","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_spanish_1e_6| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/sanchit-gandhi/whisper-small-es-1e-6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_spanish_1e_6_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_spanish_1e_6_pipeline_en.md new file mode 100644 index 00000000000000..12f2593de97f96 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_spanish_1e_6_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_small_spanish_1e_6_pipeline pipeline WhisperForCTC from sanchit-gandhi +author: John Snow Labs +name: asr_whisper_small_spanish_1e_6_pipeline +date: 2023-10-20 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_spanish_1e_6_pipeline` is a English model originally trained by sanchit-gandhi. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_spanish_1e_6_pipeline_en_5.1.4_3.4_1697760208725.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_spanish_1e_6_pipeline_en_5.1.4_3.4_1697760208725.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_spanish_1e_6_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_spanish_1e_6_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_spanish_1e_6_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/sanchit-gandhi/whisper-small-es-1e-6 + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_spanish_ari_es.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_spanish_ari_es.md new file mode 100644 index 00000000000000..11327d1825fa85 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_spanish_ari_es.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Castilian, Spanish asr_whisper_small_spanish_ari WhisperForCTC from Ari +author: John Snow Labs +name: asr_whisper_small_spanish_ari +date: 2023-10-20 +tags: [whisper, es, open_source, asr, onnx] +task: Automatic Speech Recognition +language: es +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_spanish_ari` is a Castilian, Spanish model originally trained by Ari. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_spanish_ari_es_5.1.4_3.4_1697768478107.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_spanish_ari_es_5.1.4_3.4_1697768478107.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_spanish_ari","es") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_spanish_ari","es") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_spanish_ari| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|es| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Ari/whisper-small-es \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_spanish_ari_pipeline_es.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_spanish_ari_pipeline_es.md new file mode 100644 index 00000000000000..4da02633af751f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_spanish_ari_pipeline_es.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Castilian, Spanish asr_whisper_small_spanish_ari_pipeline pipeline WhisperForCTC from Ari +author: John Snow Labs +name: asr_whisper_small_spanish_ari_pipeline +date: 2023-10-20 +tags: [whisper, es, open_source, pipeline] +task: Automatic Speech Recognition +language: es +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_spanish_ari_pipeline` is a Castilian, Spanish model originally trained by Ari. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_spanish_ari_pipeline_es_5.1.4_3.4_1697768503168.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_spanish_ari_pipeline_es_5.1.4_3.4_1697768503168.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_spanish_ari_pipeline', lang = 'es') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_spanish_ari_pipeline', lang = 'es') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_spanish_ari_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|1.7 GB| + +## References + +https://huggingface.co/Ari/whisper-small-es + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_swe2_en.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_swe2_en.md new file mode 100644 index 00000000000000..6f9044449d9568 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_swe2_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_small_swe2 WhisperForCTC from Alexao +author: John Snow Labs +name: asr_whisper_small_swe2 +date: 2023-10-20 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_swe2` is a English model originally trained by Alexao. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swe2_en_5.1.4_3.4_1697767054560.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swe2_en_5.1.4_3.4_1697767054560.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_swe2","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_swe2","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_swe2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.1 GB| + +## References + +https://huggingface.co/Alexao/whisper-small-swe2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_swe2_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_swe2_pipeline_en.md new file mode 100644 index 00000000000000..298294a1564b3d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_swe2_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_small_swe2_pipeline pipeline WhisperForCTC from Alexao +author: John Snow Labs +name: asr_whisper_small_swe2_pipeline +date: 2023-10-20 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_swe2_pipeline` is a English model originally trained by Alexao. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swe2_pipeline_en_5.1.4_3.4_1697767075304.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swe2_pipeline_en_5.1.4_3.4_1697767075304.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_swe2_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_swe2_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_swe2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.1 GB| + +## References + +https://huggingface.co/Alexao/whisper-small-swe2 + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_swedish_english_pipeline_se.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_swedish_english_pipeline_se.md new file mode 100644 index 00000000000000..f9feb96ec89d7b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_swedish_english_pipeline_se.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Northern Sami asr_whisper_small_swedish_english_pipeline pipeline WhisperForCTC from humeur +author: John Snow Labs +name: asr_whisper_small_swedish_english_pipeline +date: 2023-10-20 +tags: [whisper, se, open_source, pipeline] +task: Automatic Speech Recognition +language: se +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_swedish_english_pipeline` is a Northern Sami model originally trained by humeur. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swedish_english_pipeline_se_5.1.4_3.4_1697765615738.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swedish_english_pipeline_se_5.1.4_3.4_1697765615738.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_swedish_english_pipeline', lang = 'se') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_swedish_english_pipeline', lang = 'se') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_swedish_english_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|se| +|Size:|1.7 GB| + +## References + +https://huggingface.co/humeur/whisper-small-sv-en + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_swedish_english_se.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_swedish_english_se.md new file mode 100644 index 00000000000000..85ca6259dcf620 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_swedish_english_se.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Northern Sami asr_whisper_small_swedish_english WhisperForCTC from humeur +author: John Snow Labs +name: asr_whisper_small_swedish_english +date: 2023-10-20 +tags: [whisper, se, open_source, asr, onnx] +task: Automatic Speech Recognition +language: se +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_swedish_english` is a Northern Sami model originally trained by humeur. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swedish_english_se_5.1.4_3.4_1697765589681.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swedish_english_se_5.1.4_3.4_1697765589681.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_swedish_english","se") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_swedish_english","se") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_swedish_english| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|se| +|Size:|1.7 GB| + +## References + +https://huggingface.co/humeur/whisper-small-sv-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_swedish_torileatherman_pipeline_sv.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_swedish_torileatherman_pipeline_sv.md new file mode 100644 index 00000000000000..4689542537e5c1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_swedish_torileatherman_pipeline_sv.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Swedish asr_whisper_small_swedish_torileatherman_pipeline pipeline WhisperForCTC from torileatherman +author: John Snow Labs +name: asr_whisper_small_swedish_torileatherman_pipeline +date: 2023-10-20 +tags: [whisper, sv, open_source, pipeline] +task: Automatic Speech Recognition +language: sv +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_swedish_torileatherman_pipeline` is a Swedish model originally trained by torileatherman. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swedish_torileatherman_pipeline_sv_5.1.4_3.4_1697762905907.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swedish_torileatherman_pipeline_sv_5.1.4_3.4_1697762905907.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_small_swedish_torileatherman_pipeline', lang = 'sv') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_small_swedish_torileatherman_pipeline', lang = 'sv') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_swedish_torileatherman_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|sv| +|Size:|1.7 GB| + +## References + +https://huggingface.co/torileatherman/whisper_small_sv + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_swedish_torileatherman_sv.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_swedish_torileatherman_sv.md new file mode 100644 index 00000000000000..cc86af5841f60b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_small_swedish_torileatherman_sv.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Swedish asr_whisper_small_swedish_torileatherman WhisperForCTC from torileatherman +author: John Snow Labs +name: asr_whisper_small_swedish_torileatherman +date: 2023-10-20 +tags: [whisper, sv, open_source, asr, onnx] +task: Automatic Speech Recognition +language: sv +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_small_swedish_torileatherman` is a Swedish model originally trained by torileatherman. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swedish_torileatherman_sv_5.1.4_3.4_1697762874959.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_small_swedish_torileatherman_sv_5.1.4_3.4_1697762874959.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_small_swedish_torileatherman","sv") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_small_swedish_torileatherman","sv") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_small_swedish_torileatherman| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|sv| +|Size:|1.7 GB| + +## References + +https://huggingface.co/torileatherman/whisper_small_sv \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_testrun1_en.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_testrun1_en.md new file mode 100644 index 00000000000000..e361db61cd8204 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_testrun1_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_testrun1 WhisperForCTC from pere +author: John Snow Labs +name: asr_whisper_testrun1 +date: 2023-10-20 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_testrun1` is a English model originally trained by pere. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_testrun1_en_5.1.4_3.4_1697768297225.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_testrun1_en_5.1.4_3.4_1697768297225.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_testrun1","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_testrun1","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_testrun1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/pere/whisper-testrun1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_testrun1_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_testrun1_pipeline_en.md new file mode 100644 index 00000000000000..3cfac75c55b379 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_testrun1_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_testrun1_pipeline pipeline WhisperForCTC from pere +author: John Snow Labs +name: asr_whisper_testrun1_pipeline +date: 2023-10-20 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_testrun1_pipeline` is a English model originally trained by pere. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_testrun1_pipeline_en_5.1.4_3.4_1697768349850.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_testrun1_pipeline_en_5.1.4_3.4_1697768349850.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_testrun1_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_testrun1_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_testrun1_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|1.7 GB| + +## References + +https://huggingface.co/pere/whisper-testrun1 + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_tiny_italian_2_it.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_tiny_italian_2_it.md new file mode 100644 index 00000000000000..175a97d994bb03 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_tiny_italian_2_it.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Italian asr_whisper_tiny_italian_2 WhisperForCTC from GIanlucaRub +author: John Snow Labs +name: asr_whisper_tiny_italian_2 +date: 2023-10-20 +tags: [whisper, it, open_source, asr, onnx] +task: Automatic Speech Recognition +language: it +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_italian_2` is a Italian model originally trained by GIanlucaRub. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_italian_2_it_5.1.4_3.4_1697767694767.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_italian_2_it_5.1.4_3.4_1697767694767.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_italian_2","it") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_italian_2","it") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_italian_2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|it| +|Size:|390.8 MB| + +## References + +https://huggingface.co/GIanlucaRub/whisper-tiny-it-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_tiny_italian_2_pipeline_it.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_tiny_italian_2_pipeline_it.md new file mode 100644 index 00000000000000..f04f7ee3de55b4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_tiny_italian_2_pipeline_it.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Italian asr_whisper_tiny_italian_2_pipeline pipeline WhisperForCTC from GIanlucaRub +author: John Snow Labs +name: asr_whisper_tiny_italian_2_pipeline +date: 2023-10-20 +tags: [whisper, it, open_source, pipeline] +task: Automatic Speech Recognition +language: it +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_italian_2_pipeline` is a Italian model originally trained by GIanlucaRub. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_italian_2_pipeline_it_5.1.4_3.4_1697767702468.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_italian_2_pipeline_it_5.1.4_3.4_1697767702468.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_tiny_italian_2_pipeline', lang = 'it') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_tiny_italian_2_pipeline', lang = 'it') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_italian_2_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|it| +|Size:|390.8 MB| + +## References + +https://huggingface.co/GIanlucaRub/whisper-tiny-it-2 + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_tiny_italian_local_en.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_tiny_italian_local_en.md new file mode 100644 index 00000000000000..796e6b46ed44cc --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_tiny_italian_local_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: English asr_whisper_tiny_italian_local WhisperForCTC from GIanlucaRub +author: John Snow Labs +name: asr_whisper_tiny_italian_local +date: 2023-10-20 +tags: [whisper, en, open_source, asr, onnx] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_italian_local` is a English model originally trained by GIanlucaRub. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_italian_local_en_5.1.4_3.4_1697763349106.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_italian_local_en_5.1.4_3.4_1697763349106.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_italian_local","en") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_italian_local","en") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_italian_local| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|en| +|Size:|390.7 MB| + +## References + +https://huggingface.co/GIanlucaRub/whisper-tiny-it-local \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_tiny_italian_local_pipeline_en.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_tiny_italian_local_pipeline_en.md new file mode 100644 index 00000000000000..2e056b75cb4d5c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_tiny_italian_local_pipeline_en.md @@ -0,0 +1,71 @@ +--- +layout: model +title: English asr_whisper_tiny_italian_local_pipeline pipeline WhisperForCTC from GIanlucaRub +author: John Snow Labs +name: asr_whisper_tiny_italian_local_pipeline +date: 2023-10-20 +tags: [whisper, en, open_source, pipeline] +task: Automatic Speech Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_italian_local_pipeline` is a English model originally trained by GIanlucaRub. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_italian_local_pipeline_en_5.1.4_3.4_1697763359286.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_italian_local_pipeline_en_5.1.4_3.4_1697763359286.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_tiny_italian_local_pipeline', lang = 'en') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_tiny_italian_local_pipeline', lang = 'en') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_italian_local_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|en| +|Size:|390.7 MB| + +## References + +https://huggingface.co/GIanlucaRub/whisper-tiny-it-local + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_tiny_spanish_arpagon_es.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_tiny_spanish_arpagon_es.md new file mode 100644 index 00000000000000..798ecbeeca1171 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_tiny_spanish_arpagon_es.md @@ -0,0 +1,92 @@ +--- +layout: model +title: Castilian, Spanish asr_whisper_tiny_spanish_arpagon WhisperForCTC from arpagon +author: John Snow Labs +name: asr_whisper_tiny_spanish_arpagon +date: 2023-10-20 +tags: [whisper, es, open_source, asr, onnx] +task: Automatic Speech Recognition +language: es +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: WhisperForCTC +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_spanish_arpagon` is a Castilian, Spanish model originally trained by arpagon. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_spanish_arpagon_es_5.1.4_3.4_1697761762014.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_spanish_arpagon_es_5.1.4_3.4_1697761762014.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +audioAssembler = AudioAssembler() \ + .setInputCol("audio_content") \ + .setOutputCol("audio_assembler") + + +speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_spanish_arpagon","es") \ + .setInputCols(["audio_assembler"]) \ + .setOutputCol("text") + +pipeline = Pipeline().setStages([audioAssembler, speechToText]) + +pipelineModel = pipeline.fit(data) + +pipelineDF = pipelineModel.transform(data) + +``` +```scala + +val audioAssembler = new AudioAssembler() + .setInputCol("audio_content") + .setOutputCol("audio_assembler") + +val speechToText = WhisperForCTC.pretrained("asr_whisper_tiny_spanish_arpagon","es") + .setInputCols(Array("audio_assembler")) + .setOutputCol("text") + +val pipeline = new Pipeline().setStages(Array(audioAssembler, speechToText)) + +val pipelineModel = pipeline.fit(data) + +val pipelineDF = pipelineModel.transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_spanish_arpagon| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[audio_assembler]| +|Output Labels:|[text]| +|Language:|es| +|Size:|390.7 MB| + +## References + +https://huggingface.co/arpagon/whisper-tiny-es \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_tiny_spanish_arpagon_pipeline_es.md b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_tiny_spanish_arpagon_pipeline_es.md new file mode 100644 index 00000000000000..93c188485a8dd3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-20-asr_whisper_tiny_spanish_arpagon_pipeline_es.md @@ -0,0 +1,71 @@ +--- +layout: model +title: Castilian, Spanish asr_whisper_tiny_spanish_arpagon_pipeline pipeline WhisperForCTC from arpagon +author: John Snow Labs +name: asr_whisper_tiny_spanish_arpagon_pipeline +date: 2023-10-20 +tags: [whisper, es, open_source, pipeline] +task: Automatic Speech Recognition +language: es +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +annotator: PipelineModel +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained WhisperForCTC, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`asr_whisper_tiny_spanish_arpagon_pipeline` is a Castilian, Spanish model originally trained by arpagon. + +This model is only compatible with PySpark 3.4 and above + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_spanish_arpagon_pipeline_es_5.1.4_3.4_1697761769281.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/asr_whisper_tiny_spanish_arpagon_pipeline_es_5.1.4_3.4_1697761769281.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +pipeline = PretrainedPipeline('asr_whisper_tiny_spanish_arpagon_pipeline', lang = 'es') +annotations = pipeline.transform(audioDF) + +``` +```scala + +val pipeline = new PretrainedPipeline('asr_whisper_tiny_spanish_arpagon_pipeline', lang = 'es') +val annotations = pipeline.transform(audioDF) + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|asr_whisper_tiny_spanish_arpagon_pipeline| +|Type:|pipeline| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Language:|es| +|Size:|390.7 MB| + +## References + +https://huggingface.co/arpagon/whisper-tiny-es + +## Included Models + +- AudioAssembler +- WhisperForCTC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_arabertv2_finetuned_emotion_aetd2_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_arabertv2_finetuned_emotion_aetd2_en.md new file mode 100644 index 00000000000000..04c0d48d3d9002 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_arabertv2_finetuned_emotion_aetd2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_arabertv2_finetuned_emotion_aetd2 BertForSequenceClassification from MahaJar +author: John Snow Labs +name: bert_base_arabertv2_finetuned_emotion_aetd2 +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabertv2_finetuned_emotion_aetd2` is a English model originally trained by MahaJar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabertv2_finetuned_emotion_aetd2_en_5.1.4_3.4_1698189731931.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabertv2_finetuned_emotion_aetd2_en_5.1.4_3.4_1698189731931.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabertv2_finetuned_emotion_aetd2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabertv2_finetuned_emotion_aetd2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabertv2_finetuned_emotion_aetd2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|507.1 MB| + +## References + +https://huggingface.co/MahaJar/bert-base-arabertv2-finetuned-emotion_AETD2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_vish88_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_vish88_en.md new file mode 100644 index 00000000000000..837de051ab6f13 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_vish88_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_vish88 BertForSequenceClassification from vish88 +author: John Snow Labs +name: bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_vish88 +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_vish88` is a English model originally trained by vish88. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_vish88_en_5.1.4_3.4_1698189720514.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_vish88_en_5.1.4_3.4_1698189720514.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_vish88","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_vish88","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_vish88| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|408.6 MB| + +## References + +https://huggingface.co/vish88/bert-base-arabic-camelbert-msa-sixteenth-xnli-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_arabic_camelbert_msa_xnli_finetuned_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_arabic_camelbert_msa_xnli_finetuned_en.md new file mode 100644 index 00000000000000..f2f44c0629d4a2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_arabic_camelbert_msa_xnli_finetuned_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_arabic_camelbert_msa_xnli_finetuned BertForSequenceClassification from vish88 +author: John Snow Labs +name: bert_base_arabic_camelbert_msa_xnli_finetuned +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabic_camelbert_msa_xnli_finetuned` is a English model originally trained by vish88. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_msa_xnli_finetuned_en_5.1.4_3.4_1698189328456.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_msa_xnli_finetuned_en_5.1.4_3.4_1698189328456.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabic_camelbert_msa_xnli_finetuned","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabic_camelbert_msa_xnli_finetuned","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabic_camelbert_msa_xnli_finetuned| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|408.6 MB| + +## References + +https://huggingface.co/vish88/bert-base-arabic-camelbert-msa-xnli-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_cased_finetuned_mnli_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_cased_finetuned_mnli_en.md new file mode 100644 index 00000000000000..55d6ca542f3a83 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_cased_finetuned_mnli_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_cased_finetuned_mnli BertForSequenceClassification from George-Ogden +author: John Snow Labs +name: bert_base_cased_finetuned_mnli +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_finetuned_mnli` is a English model originally trained by George-Ogden. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_mnli_en_5.1.4_3.4_1698191244740.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_mnli_en_5.1.4_3.4_1698191244740.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_finetuned_mnli","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_finetuned_mnli","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_finetuned_mnli| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/George-Ogden/bert-base-cased-finetuned-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_cased_qqp_a_bhimany_u08_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_cased_qqp_a_bhimany_u08_en.md new file mode 100644 index 00000000000000..3a2dd707aa98b1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_cased_qqp_a_bhimany_u08_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_cased_qqp_a_bhimany_u08 BertForSequenceClassification from A-bhimany-u08 +author: John Snow Labs +name: bert_base_cased_qqp_a_bhimany_u08 +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_qqp_a_bhimany_u08` is a English model originally trained by A-bhimany-u08. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_qqp_a_bhimany_u08_en_5.1.4_3.4_1698186168859.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_qqp_a_bhimany_u08_en_5.1.4_3.4_1698186168859.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_qqp_a_bhimany_u08","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_qqp_a_bhimany_u08","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_qqp_a_bhimany_u08| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/A-bhimany-u08/bert-base-cased-qqp \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_chinese_finetuned_amazon_chinese_20000_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_chinese_finetuned_amazon_chinese_20000_en.md new file mode 100644 index 00000000000000..91f9c62aa1d79b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_chinese_finetuned_amazon_chinese_20000_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_chinese_finetuned_amazon_chinese_20000 BertForSequenceClassification from ASCCCCCCCC +author: John Snow Labs +name: bert_base_chinese_finetuned_amazon_chinese_20000 +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_finetuned_amazon_chinese_20000` is a English model originally trained by ASCCCCCCCC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_amazon_chinese_20000_en_5.1.4_3.4_1698186566662.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_amazon_chinese_20000_en_5.1.4_3.4_1698186566662.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_finetuned_amazon_chinese_20000","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_finetuned_amazon_chinese_20000","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_finetuned_amazon_chinese_20000| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/ASCCCCCCCC/bert-base-chinese-finetuned-amazon_zh_20000 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_chinese_finetuned_amazon_chinese_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_chinese_finetuned_amazon_chinese_en.md new file mode 100644 index 00000000000000..937cfb2ef582f9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_chinese_finetuned_amazon_chinese_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_chinese_finetuned_amazon_chinese BertForSequenceClassification from ASCCCCCCCC +author: John Snow Labs +name: bert_base_chinese_finetuned_amazon_chinese +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_finetuned_amazon_chinese` is a English model originally trained by ASCCCCCCCC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_amazon_chinese_en_5.1.4_3.4_1698186398104.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_amazon_chinese_en_5.1.4_3.4_1698186398104.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_finetuned_amazon_chinese","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_finetuned_amazon_chinese","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_finetuned_amazon_chinese| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/ASCCCCCCCC/bert-base-chinese-finetuned-amazon_zh \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_finetuned_sts_namvandy_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_finetuned_sts_namvandy_en.md new file mode 100644 index 00000000000000..55ee3eba15c0a1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_finetuned_sts_namvandy_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_finetuned_sts_namvandy BertForSequenceClassification from namvandy +author: John Snow Labs +name: bert_base_finetuned_sts_namvandy +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_finetuned_sts_namvandy` is a English model originally trained by namvandy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_sts_namvandy_en_5.1.4_3.4_1698188939043.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_sts_namvandy_en_5.1.4_3.4_1698188939043.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_finetuned_sts_namvandy","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_finetuned_sts_namvandy","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_finetuned_sts_namvandy| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.6 MB| + +## References + +https://huggingface.co/namvandy/bert-base-finetuned-sts \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_finetuned_sts_v3_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_finetuned_sts_v3_en.md new file mode 100644 index 00000000000000..d30ca5f8c8edf8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_finetuned_sts_v3_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_finetuned_sts_v3 BertForSequenceClassification from namvandy +author: John Snow Labs +name: bert_base_finetuned_sts_v3 +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_finetuned_sts_v3` is a English model originally trained by namvandy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_sts_v3_en_5.1.4_3.4_1698190767059.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_sts_v3_en_5.1.4_3.4_1698190767059.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_finetuned_sts_v3","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_finetuned_sts_v3","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_finetuned_sts_v3| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.6 MB| + +## References + +https://huggingface.co/namvandy/bert-base-finetuned-sts-v3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_msmarco_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_msmarco_en.md new file mode 100644 index 00000000000000..4316a2e17e53f1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_msmarco_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_msmarco BertForSequenceClassification from Capreolus +author: John Snow Labs +name: bert_base_msmarco +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_msmarco` is a English model originally trained by Capreolus. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_msmarco_en_5.1.4_3.4_1698191113313.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_msmarco_en_5.1.4_3.4_1698191113313.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_msmarco","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_msmarco","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_msmarco| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Capreolus/bert-base-msmarco \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_multilingual_cased_xnli_finetuned_xx.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_multilingual_cased_xnli_finetuned_xx.md new file mode 100644 index 00000000000000..1d09374e4007cd --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_multilingual_cased_xnli_finetuned_xx.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_xnli_finetuned BertForSequenceClassification from vish88 +author: John Snow Labs +name: bert_base_multilingual_cased_xnli_finetuned +date: 2023-10-24 +tags: [bert, xx, open_source, sequence_classification, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_xnli_finetuned` is a Multilingual model originally trained by vish88. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_xnli_finetuned_xx_5.1.4_3.4_1698189926824.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_xnli_finetuned_xx_5.1.4_3.4_1698189926824.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_cased_xnli_finetuned","xx")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_cased_xnli_finetuned","xx") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_xnli_finetuned| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/vish88/bert-base-multilingual-cased-xnli-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_spanish_wwm_cased_finetuned_emotion_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_spanish_wwm_cased_finetuned_emotion_en.md new file mode 100644 index 00000000000000..c7aa7081dfe18e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_spanish_wwm_cased_finetuned_emotion_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_spanish_wwm_cased_finetuned_emotion BertForSequenceClassification from Willy +author: John Snow Labs +name: bert_base_spanish_wwm_cased_finetuned_emotion +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_spanish_wwm_cased_finetuned_emotion` is a English model originally trained by Willy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_finetuned_emotion_en_5.1.4_3.4_1698190266410.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_finetuned_emotion_en_5.1.4_3.4_1698190266410.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_spanish_wwm_cased_finetuned_emotion","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_spanish_wwm_cased_finetuned_emotion","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_spanish_wwm_cased_finetuned_emotion| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.7 MB| + +## References + +https://huggingface.co/Willy/bert-base-spanish-wwm-cased-finetuned-emotion \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_spanish_wwm_cased_finetuned_mldoc_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_spanish_wwm_cased_finetuned_mldoc_en.md new file mode 100644 index 00000000000000..34dc1a354c34a5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_spanish_wwm_cased_finetuned_mldoc_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_spanish_wwm_cased_finetuned_mldoc BertForSequenceClassification from dccuchile +author: John Snow Labs +name: bert_base_spanish_wwm_cased_finetuned_mldoc +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_spanish_wwm_cased_finetuned_mldoc` is a English model originally trained by dccuchile. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_finetuned_mldoc_en_5.1.4_3.4_1698191298623.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_finetuned_mldoc_en_5.1.4_3.4_1698191298623.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_spanish_wwm_cased_finetuned_mldoc","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_spanish_wwm_cased_finetuned_mldoc","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_spanish_wwm_cased_finetuned_mldoc| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.7 MB| + +## References + +https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased-finetuned-mldoc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_spanish_wwm_cased_finetuned_nlp_ie_2_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_spanish_wwm_cased_finetuned_nlp_ie_2_en.md new file mode 100644 index 00000000000000..96f603e0ca7f21 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_spanish_wwm_cased_finetuned_nlp_ie_2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_spanish_wwm_cased_finetuned_nlp_ie_2 BertForSequenceClassification from Willy +author: John Snow Labs +name: bert_base_spanish_wwm_cased_finetuned_nlp_ie_2 +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_spanish_wwm_cased_finetuned_nlp_ie_2` is a English model originally trained by Willy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_finetuned_nlp_ie_2_en_5.1.4_3.4_1698191693978.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_finetuned_nlp_ie_2_en_5.1.4_3.4_1698191693978.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_spanish_wwm_cased_finetuned_nlp_ie_2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_spanish_wwm_cased_finetuned_nlp_ie_2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_spanish_wwm_cased_finetuned_nlp_ie_2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.7 MB| + +## References + +https://huggingface.co/Willy/bert-base-spanish-wwm-cased-finetuned-NLP-IE-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_spanish_wwm_cased_finetuned_pawsx_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_spanish_wwm_cased_finetuned_pawsx_en.md new file mode 100644 index 00000000000000..4a29b6f59404ef --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_spanish_wwm_cased_finetuned_pawsx_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_spanish_wwm_cased_finetuned_pawsx BertForSequenceClassification from dccuchile +author: John Snow Labs +name: bert_base_spanish_wwm_cased_finetuned_pawsx +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_spanish_wwm_cased_finetuned_pawsx` is a English model originally trained by dccuchile. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_finetuned_pawsx_en_5.1.4_3.4_1698191518128.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_finetuned_pawsx_en_5.1.4_3.4_1698191518128.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_spanish_wwm_cased_finetuned_pawsx","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_spanish_wwm_cased_finetuned_pawsx","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_spanish_wwm_cased_finetuned_pawsx| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.7 MB| + +## References + +https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased-finetuned-pawsx \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_spanish_wwm_cased_finetuned_xnli_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_spanish_wwm_cased_finetuned_xnli_en.md new file mode 100644 index 00000000000000..acb5304c4cc03e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_spanish_wwm_cased_finetuned_xnli_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_spanish_wwm_cased_finetuned_xnli BertForSequenceClassification from dccuchile +author: John Snow Labs +name: bert_base_spanish_wwm_cased_finetuned_xnli +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_spanish_wwm_cased_finetuned_xnli` is a English model originally trained by dccuchile. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_finetuned_xnli_en_5.1.4_3.4_1698191692355.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_finetuned_xnli_en_5.1.4_3.4_1698191692355.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_spanish_wwm_cased_finetuned_xnli","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_spanish_wwm_cased_finetuned_xnli","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_spanish_wwm_cased_finetuned_xnli| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.7 MB| + +## References + +https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased-finetuned-xnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_spanish_wwm_uncased_finetuned_mldoc_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_spanish_wwm_uncased_finetuned_mldoc_en.md new file mode 100644 index 00000000000000..306b44cd7bc9f1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_spanish_wwm_uncased_finetuned_mldoc_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_spanish_wwm_uncased_finetuned_mldoc BertForSequenceClassification from dccuchile +author: John Snow Labs +name: bert_base_spanish_wwm_uncased_finetuned_mldoc +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_spanish_wwm_uncased_finetuned_mldoc` is a English model originally trained by dccuchile. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_uncased_finetuned_mldoc_en_5.1.4_3.4_1698191893764.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_uncased_finetuned_mldoc_en_5.1.4_3.4_1698191893764.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_spanish_wwm_uncased_finetuned_mldoc","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_spanish_wwm_uncased_finetuned_mldoc","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_spanish_wwm_uncased_finetuned_mldoc| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.9 MB| + +## References + +https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased-finetuned-mldoc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_cola_gokuls_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_cola_gokuls_en.md new file mode 100644 index 00000000000000..3b741b6f0a1a33 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_cola_gokuls_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_cola_gokuls BertForSequenceClassification from gokuls +author: John Snow Labs +name: bert_base_uncased_cola_gokuls +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_cola_gokuls` is a English model originally trained by gokuls. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_cola_gokuls_en_5.1.4_3.4_1698187184249.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_cola_gokuls_en_5.1.4_3.4_1698187184249.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_cola_gokuls","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_cola_gokuls","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_cola_gokuls| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/gokuls/bert-base-uncased-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_emotion_amaazallahi_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_emotion_amaazallahi_en.md new file mode 100644 index 00000000000000..7a009624925ae5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_emotion_amaazallahi_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_emotion_amaazallahi BertForSequenceClassification from amaazallahi +author: John Snow Labs +name: bert_base_uncased_emotion_amaazallahi +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_emotion_amaazallahi` is a English model originally trained by amaazallahi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotion_amaazallahi_en_5.1.4_3.4_1698189530864.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotion_amaazallahi_en_5.1.4_3.4_1698189530864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_emotion_amaazallahi","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_emotion_amaazallahi","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_emotion_amaazallahi| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/amaazallahi/bert-base-uncased-emotion \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_finetuned_cola_joqsan_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_finetuned_cola_joqsan_en.md new file mode 100644 index 00000000000000..a88d4d5fb29804 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_finetuned_cola_joqsan_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_joqsan BertForSequenceClassification from Joqsan +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_joqsan +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_joqsan` is a English model originally trained by Joqsan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_joqsan_en_5.1.4_3.4_1698190334776.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_joqsan_en_5.1.4_3.4_1698190334776.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_joqsan","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_joqsan","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_joqsan| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Joqsan/bert-base-uncased-finetuned-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_finetuned_cola_richard0113_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_finetuned_cola_richard0113_en.md new file mode 100644 index 00000000000000..aaa77d7dbedd1a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_finetuned_cola_richard0113_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_richard0113 BertForSequenceClassification from Richard0113 +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_richard0113 +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_richard0113` is a English model originally trained by Richard0113. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_richard0113_en_5.1.4_3.4_1698186811781.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_richard0113_en_5.1.4_3.4_1698186811781.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_richard0113","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_richard0113","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_richard0113| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Richard0113/bert-base-uncased-finetuned-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_finetuned_mrpc_richard0113_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_finetuned_mrpc_richard0113_en.md new file mode 100644 index 00000000000000..1cbc765dfd0855 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_finetuned_mrpc_richard0113_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_mrpc_richard0113 BertForSequenceClassification from Richard0113 +author: John Snow Labs +name: bert_base_uncased_finetuned_mrpc_richard0113 +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_mrpc_richard0113` is a English model originally trained by Richard0113. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mrpc_richard0113_en_5.1.4_3.4_1698186993936.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mrpc_richard0113_en_5.1.4_3.4_1698186993936.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_mrpc_richard0113","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_mrpc_richard0113","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_mrpc_richard0113| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Richard0113/bert-base-uncased-finetuned-mrpc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_finetuned_qnli_joqsan_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_finetuned_qnli_joqsan_en.md new file mode 100644 index 00000000000000..94aec6b4eac72b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_finetuned_qnli_joqsan_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_qnli_joqsan BertForSequenceClassification from Joqsan +author: John Snow Labs +name: bert_base_uncased_finetuned_qnli_joqsan +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_qnli_joqsan` is a English model originally trained by Joqsan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_qnli_joqsan_en_5.1.4_3.4_1698191164031.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_qnli_joqsan_en_5.1.4_3.4_1698191164031.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_qnli_joqsan","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_qnli_joqsan","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_qnli_joqsan| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Joqsan/bert-base-uncased-finetuned-qnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_mnli_gokuls_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_mnli_gokuls_en.md new file mode 100644 index 00000000000000..68c349035e90cf --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_mnli_gokuls_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_mnli_gokuls BertForSequenceClassification from gokuls +author: John Snow Labs +name: bert_base_uncased_mnli_gokuls +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_mnli_gokuls` is a English model originally trained by gokuls. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mnli_gokuls_en_5.1.4_3.4_1698188725843.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mnli_gokuls_en_5.1.4_3.4_1698188725843.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_mnli_gokuls","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_mnli_gokuls","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_mnli_gokuls| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/gokuls/bert-base-uncased-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_mrpc_gokuls_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_mrpc_gokuls_en.md new file mode 100644 index 00000000000000..52ed97266c71b9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_mrpc_gokuls_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_mrpc_gokuls BertForSequenceClassification from gokuls +author: John Snow Labs +name: bert_base_uncased_mrpc_gokuls +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_mrpc_gokuls` is a English model originally trained by gokuls. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mrpc_gokuls_en_5.1.4_3.4_1698187398987.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mrpc_gokuls_en_5.1.4_3.4_1698187398987.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_mrpc_gokuls","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_mrpc_gokuls","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_mrpc_gokuls| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/gokuls/bert-base-uncased-mrpc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_nlpproject2023_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_nlpproject2023_en.md new file mode 100644 index 00000000000000..c2ab4ac558ae90 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_nlpproject2023_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_nlpproject2023 BertForSequenceClassification from nlpproject2023 +author: John Snow Labs +name: bert_base_uncased_nlpproject2023 +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_nlpproject2023` is a English model originally trained by nlpproject2023. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_nlpproject2023_en_5.1.4_3.4_1698190554359.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_nlpproject2023_en_5.1.4_3.4_1698190554359.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_nlpproject2023","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_nlpproject2023","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_nlpproject2023| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/nlpproject2023/bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_qnli_gokuls_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_qnli_gokuls_en.md new file mode 100644 index 00000000000000..aaef38ede1fd7b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_qnli_gokuls_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_qnli_gokuls BertForSequenceClassification from gokuls +author: John Snow Labs +name: bert_base_uncased_qnli_gokuls +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_qnli_gokuls` is a English model originally trained by gokuls. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_qnli_gokuls_en_5.1.4_3.4_1698187600239.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_qnli_gokuls_en_5.1.4_3.4_1698187600239.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_qnli_gokuls","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_qnli_gokuls","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_qnli_gokuls| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/gokuls/bert-base-uncased-qnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_qqp_gokuls_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_qqp_gokuls_en.md new file mode 100644 index 00000000000000..e89f385fd092ca --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_qqp_gokuls_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_qqp_gokuls BertForSequenceClassification from gokuls +author: John Snow Labs +name: bert_base_uncased_qqp_gokuls +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_qqp_gokuls` is a English model originally trained by gokuls. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_qqp_gokuls_en_5.1.4_3.4_1698187797404.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_qqp_gokuls_en_5.1.4_3.4_1698187797404.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_qqp_gokuls","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_qqp_gokuls","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_qqp_gokuls| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/gokuls/bert-base-uncased-qqp \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_rte_gokuls_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_rte_gokuls_en.md new file mode 100644 index 00000000000000..dc7492707bd923 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_rte_gokuls_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_rte_gokuls BertForSequenceClassification from gokuls +author: John Snow Labs +name: bert_base_uncased_rte_gokuls +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_rte_gokuls` is a English model originally trained by gokuls. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_rte_gokuls_en_5.1.4_3.4_1698187957658.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_rte_gokuls_en_5.1.4_3.4_1698187957658.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_rte_gokuls","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_rte_gokuls","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_rte_gokuls| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/gokuls/bert-base-uncased-rte \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_sst2_gokuls_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_sst2_gokuls_en.md new file mode 100644 index 00000000000000..8cd815eec59217 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_sst2_gokuls_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_sst2_gokuls BertForSequenceClassification from gokuls +author: John Snow Labs +name: bert_base_uncased_sst2_gokuls +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_sst2_gokuls` is a English model originally trained by gokuls. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst2_gokuls_en_5.1.4_3.4_1698188150016.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst2_gokuls_en_5.1.4_3.4_1698188150016.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst2_gokuls","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst2_gokuls","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sst2_gokuls| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/gokuls/bert-base-uncased-sst2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_stsb_gokuls_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_stsb_gokuls_en.md new file mode 100644 index 00000000000000..390a90b40c8efd --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_stsb_gokuls_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_stsb_gokuls BertForSequenceClassification from gokuls +author: John Snow Labs +name: bert_base_uncased_stsb_gokuls +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_stsb_gokuls` is a English model originally trained by gokuls. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_stsb_gokuls_en_5.1.4_3.4_1698188345394.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_stsb_gokuls_en_5.1.4_3.4_1698188345394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_stsb_gokuls","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_stsb_gokuls","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_stsb_gokuls| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/gokuls/bert-base-uncased-stsb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_wnli_gokuls_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_wnli_gokuls_en.md new file mode 100644 index 00000000000000..71e01f55f69146 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_base_uncased_wnli_gokuls_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_wnli_gokuls BertForSequenceClassification from gokuls +author: John Snow Labs +name: bert_base_uncased_wnli_gokuls +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_wnli_gokuls` is a English model originally trained by gokuls. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_wnli_gokuls_en_5.1.4_3.4_1698188535629.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_wnli_gokuls_en_5.1.4_3.4_1698188535629.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_wnli_gokuls","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_wnli_gokuls","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_wnli_gokuls| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/gokuls/bert-base-uncased-wnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_classification_lm_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_classification_lm_en.md new file mode 100644 index 00000000000000..32da58bfd7dea4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_classification_lm_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_classification_lm BertForSequenceClassification from Alireza1044 +author: John Snow Labs +name: bert_classification_lm +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classification_lm` is a English model originally trained by Alireza1044. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classification_lm_en_5.1.4_3.4_1698187102246.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classification_lm_en_5.1.4_3.4_1698187102246.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_classification_lm","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_classification_lm","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classification_lm| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Alireza1044/bert_classification_lm \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_classifier_bert_base_arabic_camelbert_msa_did_madar_twitter5_ar.md b/docs/_posts/ahmedlone127/2023-10-24-bert_classifier_bert_base_arabic_camelbert_msa_did_madar_twitter5_ar.md new file mode 100644 index 00000000000000..3443ee7a851e94 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_classifier_bert_base_arabic_camelbert_msa_did_madar_twitter5_ar.md @@ -0,0 +1,110 @@ +--- +layout: model +title: Arabic BertForSequenceClassification Base Cased model (from CAMeL-Lab) +author: John Snow Labs +name: bert_classifier_bert_base_arabic_camelbert_msa_did_madar_twitter5 +date: 2023-10-24 +tags: [ar, open_source, bert, sequence_classification, classification, onnx] +task: Text Classification +language: ar +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-arabic-camelbert-msa-did-madar-twitter5` is a Arabic model originally trained by `CAMeL-Lab`. + +## Predicted Entities + +`Palestine`, `Egypt`, `United_Arab_Emirates`, `Somalia`, `Djibouti`, `Libya`, `Tunisia`, `Bahrain`, `Jordan`, `Sudan`, `Morocco`, `Lebanon`, `Saudi_Arabia`, `Kuwait`, `Mauritania`, `Yemen`, `Qatar`, `Iraq`, `Syria`, `Algeria`, `Oman` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_bert_base_arabic_camelbert_msa_did_madar_twitter5_ar_5.1.4_3.4_1698190129293.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_bert_base_arabic_camelbert_msa_did_madar_twitter5_ar_5.1.4_3.4_1698190129293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_bert_base_arabic_camelbert_msa_did_madar_twitter5","ar") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_bert_base_arabic_camelbert_msa_did_madar_twitter5","ar") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("ar.classify.bert.twitter.base").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_bert_base_arabic_camelbert_msa_did_madar_twitter5| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|ar| +|Size:|408.6 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa-did-madar-twitter5 +- https://camel.abudhabi.nyu.edu/madar-shared-task-2019/ +- https://arxiv.org/abs/2103.06678 +- https://github.com/CAMeL-Lab/CAMeLBERT +- https://github.com/CAMeL-Lab/camel_tools \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_classifier_bert_base_arabic_camelbert_msa_poetry_ar.md b/docs/_posts/ahmedlone127/2023-10-24-bert_classifier_bert_base_arabic_camelbert_msa_poetry_ar.md new file mode 100644 index 00000000000000..94f5cb9e24d761 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_classifier_bert_base_arabic_camelbert_msa_poetry_ar.md @@ -0,0 +1,104 @@ +--- +layout: model +title: Arabic BertForSequenceClassification Base Cased model (from CAMeL-Lab) +author: John Snow Labs +name: bert_classifier_bert_base_arabic_camelbert_msa_poetry +date: 2023-10-24 +tags: [ar, open_source, bert, sequence_classification, classification, onnx] +task: Text Classification +language: ar +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-arabic-camelbert-msa-poetry` is a Arabic model originally trained by `CAMeL-Lab`. + +## Predicted Entities + +`المواليا`, `الهزج`, `المجتث`, `الدوبيت`, `البسيط`, `المتدارك`, `شعر حر`, `الرجز`, `المنسرح`, `الكامل`, `المديد`, `المقتضب`, `الوافر`, `السريع`, `المتقارب`, `الرمل`, `عامي`, `الخفيف`, `شعر التفعيلة`, `المضارع`, `الطويل`, `السلسلة`, `موشح` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_bert_base_arabic_camelbert_msa_poetry_ar_5.1.4_3.4_1698190637947.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_bert_base_arabic_camelbert_msa_poetry_ar_5.1.4_3.4_1698190637947.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_bert_base_arabic_camelbert_msa_poetry","ar") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_bert_base_arabic_camelbert_msa_poetry","ar") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_bert_base_arabic_camelbert_msa_poetry| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|ar| +|Size:|408.6 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa-poetry +- https://arxiv.org/pdf/1905.05700.pdf +- https://arxiv.org/abs/2103.06678 +- https://github.com/CAMeL-Lab/CAMeLBERT +- https://github.com/CAMeL-Lab/camel_tools \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_classifier_tiny_master_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_classifier_tiny_master_en.md new file mode 100644 index 00000000000000..03d1c8ea37ff7c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_classifier_tiny_master_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English BertForSequenceClassification Tiny Cased model (from chatwithnerd) +author: John Snow Labs +name: bert_classifier_tiny_master +date: 2023-10-24 +tags: [bert, sequence_classification, classification, open_source, en, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `tiny-bert-master-classifier` is a English model originally trained by `chatwithnerd`. + +## Predicted Entities + +`lentMoney`, `queryBudget`, `general`, `showExpenses`, `thanks`, `creditCard`, `goal`, `howWillYouTrack`, `income`, `investment`, `greeting`, `stop`, `howToEdit`, `howToAddExp`, `invalidInput`, `help`, `zeroinp`, `wtf`, `currentBalance`, `loan`, `howToAddLentMoney`, `showGoal`, `forgotSpend`, `emojiHelp`, `refund`, `questions`, `money`, `moneyPending`, `addSpend`, `edit`, `negative`, `goodbye`, `editBudgetData`, `howToAddRefund`, `cvtEMI`, `lastBudget`, `expenses`, `cashATM`, `insight`, `incompleteSpend`, `recap`, `spendAdvice` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_tiny_master_en_5.1.4_3.4_1698190774173.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_tiny_master_en_5.1.4_3.4_1698190774173.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_tiny_master","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_tiny_master","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded)) + +val data = Seq("PUT YOUR STRING HERE").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.tiny.by_chatwithnerd").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_tiny_master| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|54.3 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/chatwithnerd/tiny-bert-master-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_classifier_wiselinjayajos_finetuned_mrpc_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_classifier_wiselinjayajos_finetuned_mrpc_en.md new file mode 100644 index 00000000000000..6fa54af7dc2195 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_classifier_wiselinjayajos_finetuned_mrpc_en.md @@ -0,0 +1,107 @@ +--- +layout: model +title: English BertForSequenceClassification Cased model (from wiselinjayajos) +author: John Snow Labs +name: bert_classifier_wiselinjayajos_finetuned_mrpc +date: 2023-10-24 +tags: [bert, sequence_classification, classification, open_source, en, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `finetuned-bert-mrpc` is a English model originally trained by `wiselinjayajos`. + +## Predicted Entities + +`equivalent`, `not equivalent` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_wiselinjayajos_finetuned_mrpc_en_5.1.4_3.4_1698191206415.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_wiselinjayajos_finetuned_mrpc_en_5.1.4_3.4_1698191206415.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_wiselinjayajos_finetuned_mrpc","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_wiselinjayajos_finetuned_mrpc","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded)) + +val data = Seq("PUT YOUR STRING HERE").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.glue.finetuned.by_wiselinjayajos").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_wiselinjayajos_finetuned_mrpc| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/wiselinjayajos/finetuned-bert-mrpc +- https://paperswithcode.com/sota?task=Text+Classification&dataset=glue \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_cn_finetuning_18811449050_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_cn_finetuning_18811449050_en.md new file mode 100644 index 00000000000000..a15e2f74a24576 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_cn_finetuning_18811449050_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_cn_finetuning_18811449050 BertForSequenceClassification from 18811449050 +author: John Snow Labs +name: bert_cn_finetuning_18811449050 +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_cn_finetuning_18811449050` is a English model originally trained by 18811449050. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_cn_finetuning_18811449050_en_5.1.4_3.4_1698185823799.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_cn_finetuning_18811449050_en_5.1.4_3.4_1698185823799.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_cn_finetuning_18811449050","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_cn_finetuning_18811449050","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_cn_finetuning_18811449050| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/18811449050/bert_cn_finetuning \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_finetuned_mrpc_chunwoolee0_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_finetuned_mrpc_chunwoolee0_en.md new file mode 100644 index 00000000000000..440436366d4189 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_finetuned_mrpc_chunwoolee0_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_finetuned_mrpc_chunwoolee0 BertForSequenceClassification from chunwoolee0 +author: John Snow Labs +name: bert_finetuned_mrpc_chunwoolee0 +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_mrpc_chunwoolee0` is a English model originally trained by chunwoolee0. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_mrpc_chunwoolee0_en_5.1.4_3.4_1698190771830.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_mrpc_chunwoolee0_en_5.1.4_3.4_1698190771830.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_mrpc_chunwoolee0","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_mrpc_chunwoolee0","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_mrpc_chunwoolee0| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/chunwoolee0/bert-finetuned-mrpc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_finetuning_test_18811449050_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_finetuning_test_18811449050_en.md new file mode 100644 index 00000000000000..3e356860ba19b1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_finetuning_test_18811449050_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_finetuning_test_18811449050 BertForSequenceClassification from 18811449050 +author: John Snow Labs +name: bert_finetuning_test_18811449050 +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuning_test_18811449050` is a English model originally trained by 18811449050. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuning_test_18811449050_en_5.1.4_3.4_1698186007805.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuning_test_18811449050_en_5.1.4_3.4_1698186007805.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuning_test_18811449050","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuning_test_18811449050","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuning_test_18811449050| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/18811449050/bert_finetuning_test \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_for_sentence_identification_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_for_sentence_identification_en.md new file mode 100644 index 00000000000000..8087b084a35d5d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_for_sentence_identification_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_for_sentence_identification BertForSequenceClassification from Reza-Madani +author: John Snow Labs +name: bert_for_sentence_identification +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_for_sentence_identification` is a English model originally trained by Reza-Madani. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_for_sentence_identification_en_5.1.4_3.4_1698190138921.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_for_sentence_identification_en_5.1.4_3.4_1698190138921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_for_sentence_identification","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_for_sentence_identification","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_for_sentence_identification| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Reza-Madani/bert-for-sentence-identification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_large_cased_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_large_cased_en.md new file mode 100644 index 00000000000000..e88318b453dcdb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_large_cased_en.md @@ -0,0 +1,92 @@ +--- +layout: model +title: BERT Embeddings (Large Cased) +author: John Snow Labs +name: bert_large_cased +date: 2023-10-24 +tags: [open_source, embeddings, en, onnx] +task: Embeddings +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +This model contains a deep bidirectional transformer trained on Wikipedia and the BookCorpus. The details are described in the paper "[BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://arxiv.org/abs/1810.04805)". + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_en_5.1.4_3.4_1698191629229.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_en_5.1.4_3.4_1698191629229.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +... +embeddings = BertEmbeddings.pretrained("bert_large_cased", "en") \ +.setInputCols("sentence", "token") \ +.setOutputCol("embeddings") +nlp_pipeline = Pipeline(stages=[document_assembler, sentence_detector, tokenizer, embeddings]) +pipeline_model = nlp_pipeline.fit(spark.createDataFrame([[""]]).toDF("text")) +result = pipeline_model.transform(spark.createDataFrame([['I love NLP']], ["text"])) +``` +```scala +... +val embeddings = BertEmbeddings.pretrained("bert_large_cased", "en") +.setInputCols("sentence", "token") +.setOutputCol("embeddings") +val pipeline = new Pipeline().setStages(Array(document_assembler, sentence_detector, tokenizer, embeddings)) +val data = Seq("I love NLP").toDF("text") +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu + +text = ["I love NLP"] +embeddings_df = nlu.load('en.embed.bert.large_cased').predict(text, output_level='token') +embeddings_df +``` +
+ +## Results + +```bash + + token en_embed_bert_large_cased_embeddings + + I [-0.5893247723579407, -1.1389378309249878, -0.... + love [-0.8002289533615112, -0.15043185651302338, 0.... + NLP [-0.8995863199234009, 0.08327484875917435, 0.9... +``` + +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_cased| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_large_cased_finetuned_mnli_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_large_cased_finetuned_mnli_en.md new file mode 100644 index 00000000000000..1dae33890b9504 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_large_cased_finetuned_mnli_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_cased_finetuned_mnli BertForSequenceClassification from George-Ogden +author: John Snow Labs +name: bert_large_cased_finetuned_mnli +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_cased_finetuned_mnli` is a English model originally trained by George-Ogden. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_finetuned_mnli_en_5.1.4_3.4_1698191618840.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_finetuned_mnli_en_5.1.4_3.4_1698191618840.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_cased_finetuned_mnli","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_cased_finetuned_mnli","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_cased_finetuned_mnli| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/George-Ogden/bert-large-cased-finetuned-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_samoan_qa_abhijitt_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_samoan_qa_abhijitt_en.md new file mode 100644 index 00000000000000..c993c7512bae9f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_samoan_qa_abhijitt_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_samoan_qa_abhijitt BertForSequenceClassification from abhijitt +author: John Snow Labs +name: bert_samoan_qa_abhijitt +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_samoan_qa_abhijitt` is a English model originally trained by abhijitt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_samoan_qa_abhijitt_en_5.1.4_3.4_1698189049413.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_samoan_qa_abhijitt_en_5.1.4_3.4_1698189049413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_samoan_qa_abhijitt","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_samoan_qa_abhijitt","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_samoan_qa_abhijitt| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/abhijitt/bert_sm_qa_abhijitt \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_catalan_poetry_ar.md b/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_catalan_poetry_ar.md new file mode 100644 index 00000000000000..e8b28d9f774b3a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_catalan_poetry_ar.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Arabic bert_sequence_classifier_base_arabic_camel_catalan_poetry BertForSequenceClassification from CAMeL-Lab +author: John Snow Labs +name: bert_sequence_classifier_base_arabic_camel_catalan_poetry +date: 2023-10-24 +tags: [bert, ar, open_source, sequence_classification, onnx] +task: Text Classification +language: ar +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sequence_classifier_base_arabic_camel_catalan_poetry` is a Arabic model originally trained by CAMeL-Lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_arabic_camel_catalan_poetry_ar_5.1.4_3.4_1698187914402.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_arabic_camel_catalan_poetry_ar_5.1.4_3.4_1698187914402.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_arabic_camel_catalan_poetry","ar")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_arabic_camel_catalan_poetry","ar") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_base_arabic_camel_catalan_poetry| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|ar| +|Size:|408.9 MB| + +## References + +https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-ca-poetry \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_catalan_sentiment_ar.md b/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_catalan_sentiment_ar.md new file mode 100644 index 00000000000000..8c04664083e36a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_catalan_sentiment_ar.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Arabic bert_sequence_classifier_base_arabic_camel_catalan_sentiment BertForSequenceClassification from CAMeL-Lab +author: John Snow Labs +name: bert_sequence_classifier_base_arabic_camel_catalan_sentiment +date: 2023-10-24 +tags: [bert, ar, open_source, sequence_classification, onnx] +task: Text Classification +language: ar +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sequence_classifier_base_arabic_camel_catalan_sentiment` is a Arabic model originally trained by CAMeL-Lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_arabic_camel_catalan_sentiment_ar_5.1.4_3.4_1698188068250.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_arabic_camel_catalan_sentiment_ar_5.1.4_3.4_1698188068250.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_arabic_camel_catalan_sentiment","ar")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_arabic_camel_catalan_sentiment","ar") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_base_arabic_camel_catalan_sentiment| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|ar| +|Size:|408.8 MB| + +## References + +https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-ca-sentiment \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_danish_poetry_ar.md b/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_danish_poetry_ar.md new file mode 100644 index 00000000000000..6bc7497d8e0975 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_danish_poetry_ar.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Arabic bert_sequence_classifier_base_arabic_camel_danish_poetry BertForSequenceClassification from CAMeL-Lab +author: John Snow Labs +name: bert_sequence_classifier_base_arabic_camel_danish_poetry +date: 2023-10-24 +tags: [bert, ar, open_source, sequence_classification, onnx] +task: Text Classification +language: ar +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sequence_classifier_base_arabic_camel_danish_poetry` is a Arabic model originally trained by CAMeL-Lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_arabic_camel_danish_poetry_ar_5.1.4_3.4_1698188295579.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_arabic_camel_danish_poetry_ar_5.1.4_3.4_1698188295579.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_arabic_camel_danish_poetry","ar")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_arabic_camel_danish_poetry","ar") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_base_arabic_camel_danish_poetry| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|ar| +|Size:|409.0 MB| + +## References + +https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-da-poetry \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_danish_sentiment_ar.md b/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_danish_sentiment_ar.md new file mode 100644 index 00000000000000..dc185fef99d45a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_danish_sentiment_ar.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Arabic bert_sequence_classifier_base_arabic_camel_danish_sentiment BertForSequenceClassification from CAMeL-Lab +author: John Snow Labs +name: bert_sequence_classifier_base_arabic_camel_danish_sentiment +date: 2023-10-24 +tags: [bert, ar, open_source, sequence_classification, onnx] +task: Text Classification +language: ar +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sequence_classifier_base_arabic_camel_danish_sentiment` is a Arabic model originally trained by CAMeL-Lab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_arabic_camel_danish_sentiment_ar_5.1.4_3.4_1698188482010.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_arabic_camel_danish_sentiment_ar_5.1.4_3.4_1698188482010.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_arabic_camel_danish_sentiment","ar")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_arabic_camel_danish_sentiment","ar") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_base_arabic_camel_danish_sentiment| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|ar| +|Size:|409.0 MB| + +## References + +https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-da-sentiment \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_mix_did_madar_corpus26_ar.md b/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_mix_did_madar_corpus26_ar.md new file mode 100644 index 00000000000000..4fa7f670716593 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_mix_did_madar_corpus26_ar.md @@ -0,0 +1,104 @@ +--- +layout: model +title: Arabic BertForSequenceClassification Base Cased model (from CAMeL-Lab) +author: John Snow Labs +name: bert_sequence_classifier_base_arabic_camel_mix_did_madar_corpus26 +date: 2023-10-24 +tags: [ar, open_source, bert, sequence_classification, ner, onnx] +task: Named Entity Recognition +language: ar +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-arabic-camelbert-mix-did-madar-corpus26` is a Arabic model originally trained by `CAMeL-Lab`. + +## Predicted Entities + +`MOS`, `SAN`, `BAG`, `ALX`, `DOH`, `ALG`, `ASW`, `BEI`, `ALE`, `FES`, `KHA`, `AMM`, `TUN`, `MSA`, `JED`, `RIY`, `SFX`, `SAL`, `MUS`, `BEN`, `CAI`, `DAM`, `TRI`, `BAS`, `JER`, `RAB` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_arabic_camel_mix_did_madar_corpus26_ar_5.1.4_3.4_1698188775136.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_arabic_camel_mix_did_madar_corpus26_ar_5.1.4_3.4_1698188775136.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_arabic_camel_mix_did_madar_corpus26","ar") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_arabic_camel_mix_did_madar_corpus26","ar") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_base_arabic_camel_mix_did_madar_corpus26| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|ar| +|Size:|408.9 MB| +|Case sensitive:|true| +|Max sentence length:|128| + +## References + +References + +- https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar-corpus26 +- https://camel.abudhabi.nyu.edu/madar-shared-task-2019/ +- https://arxiv.org/abs/2103.06678 +- https://github.com/CAMeL-Lab/CAMeLBERT +- https://github.com/CAMeL-Lab/camel_tools \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_mix_did_madar_corpus6_ar.md b/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_mix_did_madar_corpus6_ar.md new file mode 100644 index 00000000000000..7b4721f932137e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_mix_did_madar_corpus6_ar.md @@ -0,0 +1,104 @@ +--- +layout: model +title: Arabic BertForSequenceClassification Base Cased model (from CAMeL-Lab) +author: John Snow Labs +name: bert_sequence_classifier_base_arabic_camel_mix_did_madar_corpus6 +date: 2023-10-24 +tags: [ar, open_source, bert, sequence_classification, ner, onnx] +task: Named Entity Recognition +language: ar +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-arabic-camelbert-mix-did-madar-corpus6` is a Arabic model originally trained by `CAMeL-Lab`. + +## Predicted Entities + +`BEI`, `TUN`, `CAI`, `MSA`, `RAB`, `DOH` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_arabic_camel_mix_did_madar_corpus6_ar_5.1.4_3.4_1698189041726.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_arabic_camel_mix_did_madar_corpus6_ar_5.1.4_3.4_1698189041726.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_arabic_camel_mix_did_madar_corpus6","ar") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_arabic_camel_mix_did_madar_corpus6","ar") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_base_arabic_camel_mix_did_madar_corpus6| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|ar| +|Size:|408.8 MB| +|Case sensitive:|true| +|Max sentence length:|128| + +## References + +References + +- https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar-corpus6 +- https://camel.abudhabi.nyu.edu/madar-shared-task-2019/ +- https://arxiv.org/abs/2103.06678 +- https://github.com/CAMeL-Lab/CAMeLBERT +- https://github.com/CAMeL-Lab/camel_tools \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_mix_did_nadi_ar.md b/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_mix_did_nadi_ar.md new file mode 100644 index 00000000000000..ea5d44d8f2694e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_mix_did_nadi_ar.md @@ -0,0 +1,104 @@ +--- +layout: model +title: Arabic BertForSequenceClassification Base Cased model (from CAMeL-Lab) +author: John Snow Labs +name: bert_sequence_classifier_base_arabic_camel_mix_did_nadi +date: 2023-10-24 +tags: [ar, open_source, bert, sequence_classification, ner, onnx] +task: Named Entity Recognition +language: ar +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-arabic-camelbert-mix-did-nadi` is a Arabic model originally trained by `CAMeL-Lab`. + +## Predicted Entities + +`Yemen`, `Bahrain`, `Djibouti`, `Algeria`, `Mauritania`, `Jordan`, `Sudan`, `Tunisia`, `Saudi_Arabia`, `United_Arab_Emirates`, `Somalia`, `Syria`, `Oman`, `Lebanon`, `Libya`, `Morocco`, `Kuwait`, `Egypt`, `Palestine`, `Qatar`, `Iraq` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_arabic_camel_mix_did_nadi_ar_5.1.4_3.4_1698189344522.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_arabic_camel_mix_did_nadi_ar_5.1.4_3.4_1698189344522.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_arabic_camel_mix_did_nadi","ar") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_arabic_camel_mix_did_nadi","ar") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_base_arabic_camel_mix_did_nadi| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|ar| +|Size:|408.9 MB| +|Case sensitive:|true| +|Max sentence length:|128| + +## References + +References + +- https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix-did-nadi +- https://sites.google.com/view/nadi-shared-task +- https://arxiv.org/abs/2103.06678 +- https://github.com/CAMeL-Lab/CAMeLBERT +- https://github.com/CAMeL-Lab/camel_tools \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_mix_poetry_ar.md b/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_mix_poetry_ar.md new file mode 100644 index 00000000000000..d47ee281e3b1e2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_mix_poetry_ar.md @@ -0,0 +1,104 @@ +--- +layout: model +title: Arabic BertForSequenceClassification Base Cased model (from CAMeL-Lab) +author: John Snow Labs +name: bert_sequence_classifier_base_arabic_camel_mix_poetry +date: 2023-10-24 +tags: [ar, open_source, bert, sequence_classification, ner, onnx] +task: Named Entity Recognition +language: ar +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-arabic-camelbert-mix-poetry` is a Arabic model originally trained by `CAMeL-Lab`. + +## Predicted Entities + +`موشح`, `الطويل`, `المنسرح`, `الهزج`, `السريع`, `المتدارك`, `السلسلة`, `عامي`, `شعر حر`, `الكامل`, `المواليا`, `الخفيف`, `المديد`, `الرجز`, `المتقارب`, `الرمل`, `المضارع`, `الدوبيت`, `المقتضب`, `الوافر`, `البسيط`, `شعر التفعيلة`, `المجتث` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_arabic_camel_mix_poetry_ar_5.1.4_3.4_1698189597404.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_arabic_camel_mix_poetry_ar_5.1.4_3.4_1698189597404.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_arabic_camel_mix_poetry","ar") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_arabic_camel_mix_poetry","ar") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_base_arabic_camel_mix_poetry| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|ar| +|Size:|408.9 MB| +|Case sensitive:|true| +|Max sentence length:|128| + +## References + +References + +- https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix-poetry +- https://arxiv.org/pdf/1905.05700.pdf +- https://arxiv.org/abs/2103.06678 +- https://github.com/CAMeL-Lab/CAMeLBERT +- https://github.com/CAMeL-Lab/camel_tools \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_mix_sentiment_ar.md b/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_mix_sentiment_ar.md new file mode 100644 index 00000000000000..b331fdc3aae2d2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_mix_sentiment_ar.md @@ -0,0 +1,107 @@ +--- +layout: model +title: Arabic BertForSequenceClassification Base Cased model (from CAMeL-Lab) +author: John Snow Labs +name: bert_sequence_classifier_base_arabic_camel_mix_sentiment +date: 2023-10-24 +tags: [ar, open_source, bert, sequence_classification, ner, onnx] +task: Named Entity Recognition +language: ar +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-arabic-camelbert-mix-sentiment` is a Arabic model originally trained by `CAMeL-Lab`. + +## Predicted Entities + +`positive`, `neutral`, `negative` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_arabic_camel_mix_sentiment_ar_5.1.4_3.4_1698189861699.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_arabic_camel_mix_sentiment_ar_5.1.4_3.4_1698189861699.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_arabic_camel_mix_sentiment","ar") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_arabic_camel_mix_sentiment","ar") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_base_arabic_camel_mix_sentiment| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|ar| +|Size:|408.8 MB| +|Case sensitive:|true| +|Max sentence length:|128| + +## References + +References + +- https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix-sentiment +- https://aclanthology.org/D15-1299.pdf +- http://lrec-conf.org/workshops/lrec2018/W30/pdf/22_W30.pdf +- https://aclanthology.org/S17-2088.pdf +- https://arxiv.org/abs/2103.06678 +- https://github.com/CAMeL-Lab/CAMeLBERT +- https://github.com/CAMeL-Lab/camel_tools +- https://github.com/CAMeL-Lab/camel_tools \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_msa_did_nadi_ar.md b/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_msa_did_nadi_ar.md new file mode 100644 index 00000000000000..89c1a9cbe35971 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_msa_did_nadi_ar.md @@ -0,0 +1,104 @@ +--- +layout: model +title: Arabic BertForSequenceClassification Base Cased model (from CAMeL-Lab) +author: John Snow Labs +name: bert_sequence_classifier_base_arabic_camel_msa_did_nadi +date: 2023-10-24 +tags: [ar, open_source, bert, sequence_classification, ner, onnx] +task: Named Entity Recognition +language: ar +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-arabic-camelbert-msa-did-nadi` is a Arabic model originally trained by `CAMeL-Lab`. + +## Predicted Entities + +`Yemen`, `Bahrain`, `Djibouti`, `Algeria`, `Mauritania`, `Jordan`, `Sudan`, `Tunisia`, `Saudi_Arabia`, `United_Arab_Emirates`, `Somalia`, `Syria`, `Oman`, `Lebanon`, `Libya`, `Morocco`, `Kuwait`, `Egypt`, `Palestine`, `Qatar`, `Iraq` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_arabic_camel_msa_did_nadi_ar_5.1.4_3.4_1698190386956.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_arabic_camel_msa_did_nadi_ar_5.1.4_3.4_1698190386956.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_arabic_camel_msa_did_nadi","ar") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_arabic_camel_msa_did_nadi","ar") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_base_arabic_camel_msa_did_nadi| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|ar| +|Size:|408.6 MB| +|Case sensitive:|true| +|Max sentence length:|128| + +## References + +References + +- https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa-did-nadi +- https://sites.google.com/view/nadi-shared-task +- https://arxiv.org/abs/2103.06678 +- https://github.com/CAMeL-Lab/CAMeLBERT +- https://github.com/CAMeL-Lab/camel_tools \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_msa_sentiment_ar.md b/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_msa_sentiment_ar.md new file mode 100644 index 00000000000000..9feec81d34c858 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_sequence_classifier_base_arabic_camel_msa_sentiment_ar.md @@ -0,0 +1,107 @@ +--- +layout: model +title: Arabic BertForSequenceClassification Base Cased model (from CAMeL-Lab) +author: John Snow Labs +name: bert_sequence_classifier_base_arabic_camel_msa_sentiment +date: 2023-10-24 +tags: [ar, open_source, bert, sequence_classification, ner, onnx] +task: Named Entity Recognition +language: ar +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-arabic-camelbert-msa-sentiment` is a Arabic model originally trained by `CAMeL-Lab`. + +## Predicted Entities + +`positive`, `neutral`, `negative` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_arabic_camel_msa_sentiment_ar_5.1.4_3.4_1698190934021.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_arabic_camel_msa_sentiment_ar_5.1.4_3.4_1698190934021.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_arabic_camel_msa_sentiment","ar") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_arabic_camel_msa_sentiment","ar") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_base_arabic_camel_msa_sentiment| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|ar| +|Size:|408.6 MB| +|Case sensitive:|true| +|Max sentence length:|128| + +## References + +References + +- https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa-sentiment +- https://aclanthology.org/D15-1299.pdf +- http://lrec-conf.org/workshops/lrec2018/W30/pdf/22_W30.pdf +- https://aclanthology.org/S17-2088.pdf +- https://arxiv.org/abs/2103.06678 +- https://github.com/CAMeL-Lab/CAMeLBERT +- https://github.com/CAMeL-Lab/camel_tools +- https://github.com/CAMeL-Lab/camel_tools \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_english_icelandic_hired_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_english_icelandic_hired_en.md new file mode 100644 index 00000000000000..70aae999a308db --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_english_icelandic_hired_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_twitter_english_icelandic_hired BertForSequenceClassification from manueltonneau +author: John Snow Labs +name: bert_twitter_english_icelandic_hired +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_twitter_english_icelandic_hired` is a English model originally trained by manueltonneau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitter_english_icelandic_hired_en_5.1.4_3.4_1698187045466.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_twitter_english_icelandic_hired_en_5.1.4_3.4_1698187045466.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_english_icelandic_hired","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_english_icelandic_hired","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_twitter_english_icelandic_hired| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.1 MB| + +## References + +https://huggingface.co/manueltonneau/bert-twitter-en-is-hired \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_english_icelandic_unemployed_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_english_icelandic_unemployed_en.md new file mode 100644 index 00000000000000..4021a2d49fadb0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_english_icelandic_unemployed_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_twitter_english_icelandic_unemployed BertForSequenceClassification from manueltonneau +author: John Snow Labs +name: bert_twitter_english_icelandic_unemployed +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_twitter_english_icelandic_unemployed` is a English model originally trained by manueltonneau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitter_english_icelandic_unemployed_en_5.1.4_3.4_1698187240391.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_twitter_english_icelandic_unemployed_en_5.1.4_3.4_1698187240391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_english_icelandic_unemployed","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_english_icelandic_unemployed","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_twitter_english_icelandic_unemployed| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.1 MB| + +## References + +https://huggingface.co/manueltonneau/bert-twitter-en-is-unemployed \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_english_job_offer_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_english_job_offer_en.md new file mode 100644 index 00000000000000..1d7c2c775806aa --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_english_job_offer_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_twitter_english_job_offer BertForSequenceClassification from manueltonneau +author: John Snow Labs +name: bert_twitter_english_job_offer +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_twitter_english_job_offer` is a English model originally trained by manueltonneau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitter_english_job_offer_en_5.1.4_3.4_1698187441524.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_twitter_english_job_offer_en_5.1.4_3.4_1698187441524.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_english_job_offer","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_english_job_offer","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_twitter_english_job_offer| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.1 MB| + +## References + +https://huggingface.co/manueltonneau/bert-twitter-en-job-offer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_english_job_search_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_english_job_search_en.md new file mode 100644 index 00000000000000..bdfe270d7e48ec --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_english_job_search_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_twitter_english_job_search BertForSequenceClassification from manueltonneau +author: John Snow Labs +name: bert_twitter_english_job_search +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_twitter_english_job_search` is a English model originally trained by manueltonneau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitter_english_job_search_en_5.1.4_3.4_1698187827004.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_twitter_english_job_search_en_5.1.4_3.4_1698187827004.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_english_job_search","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_english_job_search","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_twitter_english_job_search| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.1 MB| + +## References + +https://huggingface.co/manueltonneau/bert-twitter-en-job-search \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_english_lost_job_en.md b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_english_lost_job_en.md new file mode 100644 index 00000000000000..07c00c9a400c39 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_english_lost_job_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_twitter_english_lost_job BertForSequenceClassification from manueltonneau +author: John Snow Labs +name: bert_twitter_english_lost_job +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_twitter_english_lost_job` is a English model originally trained by manueltonneau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitter_english_lost_job_en_5.1.4_3.4_1698187626266.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_twitter_english_lost_job_en_5.1.4_3.4_1698187626266.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_english_lost_job","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_english_lost_job","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_twitter_english_lost_job| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.1 MB| + +## References + +https://huggingface.co/manueltonneau/bert-twitter-en-lost-job \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_portuguese_icelandic_hired_pt.md b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_portuguese_icelandic_hired_pt.md new file mode 100644 index 00000000000000..e56fc7b8a33e7e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_portuguese_icelandic_hired_pt.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Portuguese bert_twitter_portuguese_icelandic_hired BertForSequenceClassification from manueltonneau +author: John Snow Labs +name: bert_twitter_portuguese_icelandic_hired +date: 2023-10-24 +tags: [bert, pt, open_source, sequence_classification, onnx] +task: Text Classification +language: pt +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_twitter_portuguese_icelandic_hired` is a Portuguese model originally trained by manueltonneau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitter_portuguese_icelandic_hired_pt_5.1.4_3.4_1698189106708.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_twitter_portuguese_icelandic_hired_pt_5.1.4_3.4_1698189106708.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_portuguese_icelandic_hired","pt")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_portuguese_icelandic_hired","pt") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_twitter_portuguese_icelandic_hired| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|pt| +|Size:|408.1 MB| + +## References + +https://huggingface.co/manueltonneau/bert-twitter-pt-is-hired \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_portuguese_icelandic_unemployed_pt.md b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_portuguese_icelandic_unemployed_pt.md new file mode 100644 index 00000000000000..94d440f47f10d8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_portuguese_icelandic_unemployed_pt.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Portuguese bert_twitter_portuguese_icelandic_unemployed BertForSequenceClassification from manueltonneau +author: John Snow Labs +name: bert_twitter_portuguese_icelandic_unemployed +date: 2023-10-24 +tags: [bert, pt, open_source, sequence_classification, onnx] +task: Text Classification +language: pt +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_twitter_portuguese_icelandic_unemployed` is a Portuguese model originally trained by manueltonneau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitter_portuguese_icelandic_unemployed_pt_5.1.4_3.4_1698189297437.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_twitter_portuguese_icelandic_unemployed_pt_5.1.4_3.4_1698189297437.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_portuguese_icelandic_unemployed","pt")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_portuguese_icelandic_unemployed","pt") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_twitter_portuguese_icelandic_unemployed| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|pt| +|Size:|408.1 MB| + +## References + +https://huggingface.co/manueltonneau/bert-twitter-pt-is-unemployed \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_portuguese_job_offer_pt.md b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_portuguese_job_offer_pt.md new file mode 100644 index 00000000000000..576855be9ca1f7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_portuguese_job_offer_pt.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Portuguese bert_twitter_portuguese_job_offer BertForSequenceClassification from manueltonneau +author: John Snow Labs +name: bert_twitter_portuguese_job_offer +date: 2023-10-24 +tags: [bert, pt, open_source, sequence_classification, onnx] +task: Text Classification +language: pt +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_twitter_portuguese_job_offer` is a Portuguese model originally trained by manueltonneau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitter_portuguese_job_offer_pt_5.1.4_3.4_1698189477797.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_twitter_portuguese_job_offer_pt_5.1.4_3.4_1698189477797.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_portuguese_job_offer","pt")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_portuguese_job_offer","pt") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_twitter_portuguese_job_offer| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|pt| +|Size:|408.1 MB| + +## References + +https://huggingface.co/manueltonneau/bert-twitter-pt-job-offer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_portuguese_job_search_pt.md b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_portuguese_job_search_pt.md new file mode 100644 index 00000000000000..22a6e504d168d9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_portuguese_job_search_pt.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Portuguese bert_twitter_portuguese_job_search BertForSequenceClassification from manueltonneau +author: John Snow Labs +name: bert_twitter_portuguese_job_search +date: 2023-10-24 +tags: [bert, pt, open_source, sequence_classification, onnx] +task: Text Classification +language: pt +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_twitter_portuguese_job_search` is a Portuguese model originally trained by manueltonneau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitter_portuguese_job_search_pt_5.1.4_3.4_1698189662967.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_twitter_portuguese_job_search_pt_5.1.4_3.4_1698189662967.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_portuguese_job_search","pt")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_portuguese_job_search","pt") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_twitter_portuguese_job_search| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|pt| +|Size:|408.1 MB| + +## References + +https://huggingface.co/manueltonneau/bert-twitter-pt-job-search \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_portuguese_lost_job_pt.md b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_portuguese_lost_job_pt.md new file mode 100644 index 00000000000000..65330ec1eeaa14 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_portuguese_lost_job_pt.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Portuguese bert_twitter_portuguese_lost_job BertForSequenceClassification from manueltonneau +author: John Snow Labs +name: bert_twitter_portuguese_lost_job +date: 2023-10-24 +tags: [bert, pt, open_source, sequence_classification, onnx] +task: Text Classification +language: pt +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_twitter_portuguese_lost_job` is a Portuguese model originally trained by manueltonneau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitter_portuguese_lost_job_pt_5.1.4_3.4_1698188934801.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_twitter_portuguese_lost_job_pt_5.1.4_3.4_1698188934801.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_portuguese_lost_job","pt")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_portuguese_lost_job","pt") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_twitter_portuguese_lost_job| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|pt| +|Size:|408.1 MB| + +## References + +https://huggingface.co/manueltonneau/bert-twitter-pt-lost-job \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_spanish_icelandic_hired_es.md b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_spanish_icelandic_hired_es.md new file mode 100644 index 00000000000000..acc1092f848f5c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_spanish_icelandic_hired_es.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Castilian, Spanish bert_twitter_spanish_icelandic_hired BertForSequenceClassification from manueltonneau +author: John Snow Labs +name: bert_twitter_spanish_icelandic_hired +date: 2023-10-24 +tags: [bert, es, open_source, sequence_classification, onnx] +task: Text Classification +language: es +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_twitter_spanish_icelandic_hired` is a Castilian, Spanish model originally trained by manueltonneau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitter_spanish_icelandic_hired_es_5.1.4_3.4_1698188017171.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_twitter_spanish_icelandic_hired_es_5.1.4_3.4_1698188017171.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_spanish_icelandic_hired","es")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_spanish_icelandic_hired","es") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_twitter_spanish_icelandic_hired| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|es| +|Size:|411.7 MB| + +## References + +https://huggingface.co/manueltonneau/bert-twitter-es-is-hired \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_spanish_icelandic_unemployed_es.md b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_spanish_icelandic_unemployed_es.md new file mode 100644 index 00000000000000..1c8e84760b1cef --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_spanish_icelandic_unemployed_es.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Castilian, Spanish bert_twitter_spanish_icelandic_unemployed BertForSequenceClassification from manueltonneau +author: John Snow Labs +name: bert_twitter_spanish_icelandic_unemployed +date: 2023-10-24 +tags: [bert, es, open_source, sequence_classification, onnx] +task: Text Classification +language: es +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_twitter_spanish_icelandic_unemployed` is a Castilian, Spanish model originally trained by manueltonneau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitter_spanish_icelandic_unemployed_es_5.1.4_3.4_1698188359353.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_twitter_spanish_icelandic_unemployed_es_5.1.4_3.4_1698188359353.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_spanish_icelandic_unemployed","es")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_spanish_icelandic_unemployed","es") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_twitter_spanish_icelandic_unemployed| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|es| +|Size:|411.7 MB| + +## References + +https://huggingface.co/manueltonneau/bert-twitter-es-is-unemployed \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_spanish_job_offer_es.md b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_spanish_job_offer_es.md new file mode 100644 index 00000000000000..802e0cdaf03ca1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_spanish_job_offer_es.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Castilian, Spanish bert_twitter_spanish_job_offer BertForSequenceClassification from manueltonneau +author: John Snow Labs +name: bert_twitter_spanish_job_offer +date: 2023-10-24 +tags: [bert, es, open_source, sequence_classification, onnx] +task: Text Classification +language: es +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_twitter_spanish_job_offer` is a Castilian, Spanish model originally trained by manueltonneau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitter_spanish_job_offer_es_5.1.4_3.4_1698188539277.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_twitter_spanish_job_offer_es_5.1.4_3.4_1698188539277.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_spanish_job_offer","es")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_spanish_job_offer","es") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_twitter_spanish_job_offer| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|es| +|Size:|411.7 MB| + +## References + +https://huggingface.co/manueltonneau/bert-twitter-es-job-offer \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_spanish_job_search_es.md b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_spanish_job_search_es.md new file mode 100644 index 00000000000000..03698990d3f96c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_spanish_job_search_es.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Castilian, Spanish bert_twitter_spanish_job_search BertForSequenceClassification from manueltonneau +author: John Snow Labs +name: bert_twitter_spanish_job_search +date: 2023-10-24 +tags: [bert, es, open_source, sequence_classification, onnx] +task: Text Classification +language: es +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_twitter_spanish_job_search` is a Castilian, Spanish model originally trained by manueltonneau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitter_spanish_job_search_es_5.1.4_3.4_1698188726169.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_twitter_spanish_job_search_es_5.1.4_3.4_1698188726169.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_spanish_job_search","es")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_spanish_job_search","es") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_twitter_spanish_job_search| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|es| +|Size:|411.7 MB| + +## References + +https://huggingface.co/manueltonneau/bert-twitter-es-job-search \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_spanish_lost_job_es.md b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_spanish_lost_job_es.md new file mode 100644 index 00000000000000..2ac5a6761640dd --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-bert_twitter_spanish_lost_job_es.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Castilian, Spanish bert_twitter_spanish_lost_job BertForSequenceClassification from manueltonneau +author: John Snow Labs +name: bert_twitter_spanish_lost_job +date: 2023-10-24 +tags: [bert, es, open_source, sequence_classification, onnx] +task: Text Classification +language: es +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_twitter_spanish_lost_job` is a Castilian, Spanish model originally trained by manueltonneau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_twitter_spanish_lost_job_es_5.1.4_3.4_1698188207227.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_twitter_spanish_lost_job_es_5.1.4_3.4_1698188207227.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_spanish_lost_job","es")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_twitter_spanish_lost_job","es") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_twitter_spanish_lost_job| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|es| +|Size:|411.7 MB| + +## References + +https://huggingface.co/manueltonneau/bert-twitter-es-lost-job \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-burmese_bert_ansh_en.md b/docs/_posts/ahmedlone127/2023-10-24-burmese_bert_ansh_en.md new file mode 100644 index 00000000000000..2d07fb46e50737 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-burmese_bert_ansh_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English burmese_bert_ansh BertForSequenceClassification from Ansh +author: John Snow Labs +name: burmese_bert_ansh +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_bert_ansh` is a English model originally trained by Ansh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_bert_ansh_en_5.1.4_3.4_1698191922897.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_bert_ansh_en_5.1.4_3.4_1698191922897.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("burmese_bert_ansh","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("burmese_bert_ansh","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_bert_ansh| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Ansh/my_bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-burmese_paircls_klue_nli_beomi_kcbert_base_model_en.md b/docs/_posts/ahmedlone127/2023-10-24-burmese_paircls_klue_nli_beomi_kcbert_base_model_en.md new file mode 100644 index 00000000000000..6e070a4304a1e2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-burmese_paircls_klue_nli_beomi_kcbert_base_model_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English burmese_paircls_klue_nli_beomi_kcbert_base_model BertForSequenceClassification from chunwoolee0 +author: John Snow Labs +name: burmese_paircls_klue_nli_beomi_kcbert_base_model +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_paircls_klue_nli_beomi_kcbert_base_model` is a English model originally trained by chunwoolee0. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_paircls_klue_nli_beomi_kcbert_base_model_en_5.1.4_3.4_1698188605271.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_paircls_klue_nli_beomi_kcbert_base_model_en_5.1.4_3.4_1698188605271.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("burmese_paircls_klue_nli_beomi_kcbert_base_model","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("burmese_paircls_klue_nli_beomi_kcbert_base_model","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_paircls_klue_nli_beomi_kcbert_base_model| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|408.4 MB| + +## References + +https://huggingface.co/chunwoolee0/my_paircls_klue_nli_beomi_kcbert_base_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-covid_augment_tweet_bert_large_e2_v2_en.md b/docs/_posts/ahmedlone127/2023-10-24-covid_augment_tweet_bert_large_e2_v2_en.md new file mode 100644 index 00000000000000..67bdce85320dc4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-covid_augment_tweet_bert_large_e2_v2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English covid_augment_tweet_bert_large_e2_v2 BertForSequenceClassification from JerryYanJiang +author: John Snow Labs +name: covid_augment_tweet_bert_large_e2_v2 +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_augment_tweet_bert_large_e2_v2` is a English model originally trained by JerryYanJiang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_augment_tweet_bert_large_e2_v2_en_5.1.4_3.4_1698186896527.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_augment_tweet_bert_large_e2_v2_en_5.1.4_3.4_1698186896527.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("covid_augment_tweet_bert_large_e2_v2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("covid_augment_tweet_bert_large_e2_v2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|covid_augment_tweet_bert_large_e2_v2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/JerryYanJiang/covid-augment-tweet-bert-large-e2-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-covid_augment_tweet_bert_large_e2_version2_en.md b/docs/_posts/ahmedlone127/2023-10-24-covid_augment_tweet_bert_large_e2_version2_en.md new file mode 100644 index 00000000000000..d9cd4da2fff74f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-covid_augment_tweet_bert_large_e2_version2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English covid_augment_tweet_bert_large_e2_version2 BertForSequenceClassification from JerryYanJiang +author: John Snow Labs +name: covid_augment_tweet_bert_large_e2_version2 +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_augment_tweet_bert_large_e2_version2` is a English model originally trained by JerryYanJiang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_augment_tweet_bert_large_e2_version2_en_5.1.4_3.4_1698187597852.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_augment_tweet_bert_large_e2_version2_en_5.1.4_3.4_1698187597852.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("covid_augment_tweet_bert_large_e2_version2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("covid_augment_tweet_bert_large_e2_version2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|covid_augment_tweet_bert_large_e2_version2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/JerryYanJiang/covid-augment-tweet-bert-large-e2-version2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-covid_augment_tweet_bert_large_e2_version2_noweight_en.md b/docs/_posts/ahmedlone127/2023-10-24-covid_augment_tweet_bert_large_e2_version2_noweight_en.md new file mode 100644 index 00000000000000..2bf68e0cc8c416 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-covid_augment_tweet_bert_large_e2_version2_noweight_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English covid_augment_tweet_bert_large_e2_version2_noweight BertForSequenceClassification from JerryYanJiang +author: John Snow Labs +name: covid_augment_tweet_bert_large_e2_version2_noweight +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_augment_tweet_bert_large_e2_version2_noweight` is a English model originally trained by JerryYanJiang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_augment_tweet_bert_large_e2_version2_noweight_en_5.1.4_3.4_1698188314567.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_augment_tweet_bert_large_e2_version2_noweight_en_5.1.4_3.4_1698188314567.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("covid_augment_tweet_bert_large_e2_version2_noweight","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("covid_augment_tweet_bert_large_e2_version2_noweight","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|covid_augment_tweet_bert_large_e2_version2_noweight| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/JerryYanJiang/covid-augment-tweet-bert-large-e2-version2-noweight \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-covid_augment_tweet_bert_large_e3_v2_en.md b/docs/_posts/ahmedlone127/2023-10-24-covid_augment_tweet_bert_large_e3_v2_en.md new file mode 100644 index 00000000000000..486a2bde087ca9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-covid_augment_tweet_bert_large_e3_v2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English covid_augment_tweet_bert_large_e3_v2 BertForSequenceClassification from JerryYanJiang +author: John Snow Labs +name: covid_augment_tweet_bert_large_e3_v2 +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_augment_tweet_bert_large_e3_v2` is a English model originally trained by JerryYanJiang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_augment_tweet_bert_large_e3_v2_en_5.1.4_3.4_1698187235715.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_augment_tweet_bert_large_e3_v2_en_5.1.4_3.4_1698187235715.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("covid_augment_tweet_bert_large_e3_v2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("covid_augment_tweet_bert_large_e3_v2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|covid_augment_tweet_bert_large_e3_v2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/JerryYanJiang/covid-augment-tweet-bert-large-e3-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-covid_augment_tweet_bert_large_e4_v2_en.md b/docs/_posts/ahmedlone127/2023-10-24-covid_augment_tweet_bert_large_e4_v2_en.md new file mode 100644 index 00000000000000..a30f91f87c3bd2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-covid_augment_tweet_bert_large_e4_v2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English covid_augment_tweet_bert_large_e4_v2 BertForSequenceClassification from JerryYanJiang +author: John Snow Labs +name: covid_augment_tweet_bert_large_e4_v2 +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_augment_tweet_bert_large_e4_v2` is a English model originally trained by JerryYanJiang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_augment_tweet_bert_large_e4_v2_en_5.1.4_3.4_1698186540209.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_augment_tweet_bert_large_e4_v2_en_5.1.4_3.4_1698186540209.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("covid_augment_tweet_bert_large_e4_v2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("covid_augment_tweet_bert_large_e4_v2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|covid_augment_tweet_bert_large_e4_v2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/JerryYanJiang/covid-augment-tweet-bert-large-e4-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-covid_augment_tweet_bert_large_e8_noweight_en.md b/docs/_posts/ahmedlone127/2023-10-24-covid_augment_tweet_bert_large_e8_noweight_en.md new file mode 100644 index 00000000000000..6055b0537c5deb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-covid_augment_tweet_bert_large_e8_noweight_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English covid_augment_tweet_bert_large_e8_noweight BertForSequenceClassification from JerryYanJiang +author: John Snow Labs +name: covid_augment_tweet_bert_large_e8_noweight +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_augment_tweet_bert_large_e8_noweight` is a English model originally trained by JerryYanJiang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_augment_tweet_bert_large_e8_noweight_en_5.1.4_3.4_1698188957419.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_augment_tweet_bert_large_e8_noweight_en_5.1.4_3.4_1698188957419.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("covid_augment_tweet_bert_large_e8_noweight","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("covid_augment_tweet_bert_large_e8_noweight","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|covid_augment_tweet_bert_large_e8_noweight| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/JerryYanJiang/covid-augment-tweet-bert-large-e8-noweight \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-covid_tweet_bert_large_e2_noweight_en.md b/docs/_posts/ahmedlone127/2023-10-24-covid_tweet_bert_large_e2_noweight_en.md new file mode 100644 index 00000000000000..e67278e0e5e4a6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-covid_tweet_bert_large_e2_noweight_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English covid_tweet_bert_large_e2_noweight BertForSequenceClassification from JerryYanJiang +author: John Snow Labs +name: covid_tweet_bert_large_e2_noweight +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_tweet_bert_large_e2_noweight` is a English model originally trained by JerryYanJiang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_tweet_bert_large_e2_noweight_en_5.1.4_3.4_1698189318072.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_tweet_bert_large_e2_noweight_en_5.1.4_3.4_1698189318072.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("covid_tweet_bert_large_e2_noweight","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("covid_tweet_bert_large_e2_noweight","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|covid_tweet_bert_large_e2_noweight| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/JerryYanJiang/covid-tweet-bert-large-e2-noweight \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-distilbert_base_chinese_amazon_chinese_20000_en.md b/docs/_posts/ahmedlone127/2023-10-24-distilbert_base_chinese_amazon_chinese_20000_en.md new file mode 100644 index 00000000000000..b171e29ce7da57 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-distilbert_base_chinese_amazon_chinese_20000_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English distilbert_base_chinese_amazon_chinese_20000 BertForSequenceClassification from ASCCCCCCCC +author: John Snow Labs +name: distilbert_base_chinese_amazon_chinese_20000 +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distilbert_base_chinese_amazon_chinese_20000` is a English model originally trained by ASCCCCCCCC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distilbert_base_chinese_amazon_chinese_20000_en_5.1.4_3.4_1698186749914.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distilbert_base_chinese_amazon_chinese_20000_en_5.1.4_3.4_1698186749914.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("distilbert_base_chinese_amazon_chinese_20000","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("distilbert_base_chinese_amazon_chinese_20000","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distilbert_base_chinese_amazon_chinese_20000| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/ASCCCCCCCC/distilbert-base-chinese-amazon_zh_20000 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-hebert_finetuned_hebrew_metaphor_he.md b/docs/_posts/ahmedlone127/2023-10-24-hebert_finetuned_hebrew_metaphor_he.md new file mode 100644 index 00000000000000..5ead8da85f6c91 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-hebert_finetuned_hebrew_metaphor_he.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Hebrew hebert_finetuned_hebrew_metaphor BertForSequenceClassification from tdklab +author: John Snow Labs +name: hebert_finetuned_hebrew_metaphor +date: 2023-10-24 +tags: [bert, he, open_source, sequence_classification, onnx] +task: Text Classification +language: he +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hebert_finetuned_hebrew_metaphor` is a Hebrew model originally trained by tdklab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hebert_finetuned_hebrew_metaphor_he_5.1.4_3.4_1698190967230.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hebert_finetuned_hebrew_metaphor_he_5.1.4_3.4_1698190967230.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("hebert_finetuned_hebrew_metaphor","he")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("hebert_finetuned_hebrew_metaphor","he") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hebert_finetuned_hebrew_metaphor| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|he| +|Size:|410.3 MB| + +## References + +https://huggingface.co/tdklab/hebert-finetuned-hebrew-metaphor \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-kindword_klue_bert_base_en.md b/docs/_posts/ahmedlone127/2023-10-24-kindword_klue_bert_base_en.md new file mode 100644 index 00000000000000..ba74f272e2b265 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-kindword_klue_bert_base_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English kindword_klue_bert_base BertForSequenceClassification from powerwarez +author: John Snow Labs +name: kindword_klue_bert_base +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kindword_klue_bert_base` is a English model originally trained by powerwarez. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kindword_klue_bert_base_en_5.1.4_3.4_1698190959059.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kindword_klue_bert_base_en_5.1.4_3.4_1698190959059.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("kindword_klue_bert_base","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("kindword_klue_bert_base","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kindword_klue_bert_base| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.6 MB| + +## References + +https://huggingface.co/powerwarez/kindword-klue_bert-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-me_hate_bert_mr.md b/docs/_posts/ahmedlone127/2023-10-24-me_hate_bert_mr.md new file mode 100644 index 00000000000000..286e5f0fc38196 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-me_hate_bert_mr.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Marathi me_hate_bert BertForSequenceClassification from l3cube-pune +author: John Snow Labs +name: me_hate_bert +date: 2023-10-24 +tags: [bert, mr, open_source, sequence_classification, onnx] +task: Text Classification +language: mr +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`me_hate_bert` is a Marathi model originally trained by l3cube-pune. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/me_hate_bert_mr_5.1.4_3.4_1698190564789.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/me_hate_bert_mr_5.1.4_3.4_1698190564789.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("me_hate_bert","mr")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("me_hate_bert","mr") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|me_hate_bert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|mr| +|Size:|892.8 MB| + +## References + +https://huggingface.co/l3cube-pune/me-hate-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-norbert2_sentiment_test1_no.md b/docs/_posts/ahmedlone127/2023-10-24-norbert2_sentiment_test1_no.md new file mode 100644 index 00000000000000..6c4082192494c7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-norbert2_sentiment_test1_no.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Norwegian norbert2_sentiment_test1 BertForSequenceClassification from marcuskd +author: John Snow Labs +name: norbert2_sentiment_test1 +date: 2023-10-24 +tags: [bert, "no", open_source, sequence_classification, onnx] +task: Text Classification +language: "no" +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norbert2_sentiment_test1` is a Norwegian model originally trained by marcuskd. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_test1_no_5.1.4_3.4_1698191963919.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_test1_no_5.1.4_3.4_1698191963919.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_test1","no")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_test1","no") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norbert2_sentiment_test1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|no| +|Size:|467.4 MB| + +## References + +https://huggingface.co/marcuskd/norbert2_sentiment_test1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-parlbert_topic_german_de.md b/docs/_posts/ahmedlone127/2023-10-24-parlbert_topic_german_de.md new file mode 100644 index 00000000000000..647134d01903d1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-parlbert_topic_german_de.md @@ -0,0 +1,97 @@ +--- +layout: model +title: German parlbert_topic_german BertForSequenceClassification from chkla +author: John Snow Labs +name: parlbert_topic_german +date: 2023-10-24 +tags: [bert, de, open_source, sequence_classification, onnx] +task: Text Classification +language: de +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`parlbert_topic_german` is a German model originally trained by chkla. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/parlbert_topic_german_de_5.1.4_3.4_1698191970215.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/parlbert_topic_german_de_5.1.4_3.4_1698191970215.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("parlbert_topic_german","de")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("parlbert_topic_german","de") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|parlbert_topic_german| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|de| +|Size:|409.1 MB| + +## References + +https://huggingface.co/chkla/parlbert-topic-german \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-procedure_classification_bert_en.md b/docs/_posts/ahmedlone127/2023-10-24-procedure_classification_bert_en.md new file mode 100644 index 00000000000000..0e0e2be3bfb702 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-procedure_classification_bert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English procedure_classification_bert BertForSequenceClassification from cynthiachan +author: John Snow Labs +name: procedure_classification_bert +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`procedure_classification_bert` is a English model originally trained by cynthiachan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/procedure_classification_bert_en_5.1.4_3.4_1698186868680.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/procedure_classification_bert_en_5.1.4_3.4_1698186868680.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("procedure_classification_bert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("procedure_classification_bert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|procedure_classification_bert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.9 MB| + +## References + +https://huggingface.co/cynthiachan/procedure_classification_bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-procedure_classification_distilbert_en.md b/docs/_posts/ahmedlone127/2023-10-24-procedure_classification_distilbert_en.md new file mode 100644 index 00000000000000..9c1b47777d0392 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-procedure_classification_distilbert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English procedure_classification_distilbert BertForSequenceClassification from cynthiachan +author: John Snow Labs +name: procedure_classification_distilbert +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`procedure_classification_distilbert` is a English model originally trained by cynthiachan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/procedure_classification_distilbert_en_5.1.4_3.4_1698186706098.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/procedure_classification_distilbert_en_5.1.4_3.4_1698186706098.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("procedure_classification_distilbert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("procedure_classification_distilbert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|procedure_classification_distilbert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.9 MB| + +## References + +https://huggingface.co/cynthiachan/procedure_classification_distilbert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-qqp_bert_en.md b/docs/_posts/ahmedlone127/2023-10-24-qqp_bert_en.md new file mode 100644 index 00000000000000..90587103bd068e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-qqp_bert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English qqp_bert BertForSequenceClassification from AnonARR +author: John Snow Labs +name: qqp_bert +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`qqp_bert` is a English model originally trained by AnonARR. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/qqp_bert_en_5.1.4_3.4_1698187280591.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/qqp_bert_en_5.1.4_3.4_1698187280591.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("qqp_bert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("qqp_bert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|qqp_bert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/AnonARR/qqp-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-roberta_base_culinary_finetuned_en.md b/docs/_posts/ahmedlone127/2023-10-24-roberta_base_culinary_finetuned_en.md new file mode 100644 index 00000000000000..459f028bf75e99 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-roberta_base_culinary_finetuned_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English roberta_base_culinary_finetuned BertForSequenceClassification from juancavallotti +author: John Snow Labs +name: roberta_base_culinary_finetuned +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_base_culinary_finetuned` is a English model originally trained by juancavallotti. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_base_culinary_finetuned_en_5.1.4_3.4_1698190745728.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_base_culinary_finetuned_en_5.1.4_3.4_1698190745728.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("roberta_base_culinary_finetuned","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("roberta_base_culinary_finetuned","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_base_culinary_finetuned| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|408.8 MB| + +## References + +https://huggingface.co/juancavallotti/roberta-base-culinary-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-sentence_bert_base_uncased_finetuned_sentence_en.md b/docs/_posts/ahmedlone127/2023-10-24-sentence_bert_base_uncased_finetuned_sentence_en.md new file mode 100644 index 00000000000000..73e6996e1a959b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-sentence_bert_base_uncased_finetuned_sentence_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English sentence_bert_base_uncased_finetuned_sentence BertForSequenceClassification from ali2066 +author: John Snow Labs +name: sentence_bert_base_uncased_finetuned_sentence +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentence_bert_base_uncased_finetuned_sentence` is a English model originally trained by ali2066. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentence_bert_base_uncased_finetuned_sentence_en_5.1.4_3.4_1698190641727.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentence_bert_base_uncased_finetuned_sentence_en_5.1.4_3.4_1698190641727.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("sentence_bert_base_uncased_finetuned_sentence","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("sentence_bert_base_uncased_finetuned_sentence","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentence_bert_base_uncased_finetuned_sentence| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ali2066/sentence_bert-base-uncased-finetuned-SENTENCE \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-seqcls_mrpc_bert_base_uncased_model_en.md b/docs/_posts/ahmedlone127/2023-10-24-seqcls_mrpc_bert_base_uncased_model_en.md new file mode 100644 index 00000000000000..2b1080f10ab0a7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-seqcls_mrpc_bert_base_uncased_model_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English seqcls_mrpc_bert_base_uncased_model BertForSequenceClassification from chunwoolee0 +author: John Snow Labs +name: seqcls_mrpc_bert_base_uncased_model +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`seqcls_mrpc_bert_base_uncased_model` is a English model originally trained by chunwoolee0. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/seqcls_mrpc_bert_base_uncased_model_en_5.1.4_3.4_1698189530792.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/seqcls_mrpc_bert_base_uncased_model_en_5.1.4_3.4_1698189530792.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("seqcls_mrpc_bert_base_uncased_model","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("seqcls_mrpc_bert_base_uncased_model","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|seqcls_mrpc_bert_base_uncased_model| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/chunwoolee0/seqcls_mrpc_bert_base_uncased_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-spanbert_base_cased_en.md b/docs/_posts/ahmedlone127/2023-10-24-spanbert_base_cased_en.md new file mode 100644 index 00000000000000..ede4dd6e53160e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-spanbert_base_cased_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English spanbert_base_cased BertForSequenceClassification from ahmetayrnc +author: John Snow Labs +name: spanbert_base_cased +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`spanbert_base_cased` is a English model originally trained by ahmetayrnc. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/spanbert_base_cased_en_5.1.4_3.4_1698190962914.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/spanbert_base_cased_en_5.1.4_3.4_1698190962914.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("spanbert_base_cased","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("spanbert_base_cased","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|spanbert_base_cased| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|395.1 MB| + +## References + +https://huggingface.co/ahmetayrnc/spanbert-base-cased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-tiny_bert_sst2_distilled_suryabhan_en.md b/docs/_posts/ahmedlone127/2023-10-24-tiny_bert_sst2_distilled_suryabhan_en.md new file mode 100644 index 00000000000000..d4bffb60f948bb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-tiny_bert_sst2_distilled_suryabhan_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tiny_bert_sst2_distilled_suryabhan BertForSequenceClassification from Suryabhan +author: John Snow Labs +name: tiny_bert_sst2_distilled_suryabhan +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_sst2_distilled_suryabhan` is a English model originally trained by Suryabhan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_sst2_distilled_suryabhan_en_5.1.4_3.4_1698191313464.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_sst2_distilled_suryabhan_en_5.1.4_3.4_1698191313464.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_sst2_distilled_suryabhan","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_sst2_distilled_suryabhan","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_sst2_distilled_suryabhan| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/Suryabhan/tiny-bert-sst2-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-24-waray_philippines_tiny_bert_en.md b/docs/_posts/ahmedlone127/2023-10-24-waray_philippines_tiny_bert_en.md new file mode 100644 index 00000000000000..65a47825006224 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-24-waray_philippines_tiny_bert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English waray_philippines_tiny_bert BertForSequenceClassification from lizaboiarchuk +author: John Snow Labs +name: waray_philippines_tiny_bert +date: 2023-10-24 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`waray_philippines_tiny_bert` is a English model originally trained by lizaboiarchuk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/waray_philippines_tiny_bert_en_5.1.4_3.4_1698191755543.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/waray_philippines_tiny_bert_en_5.1.4_3.4_1698191755543.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("waray_philippines_tiny_bert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("waray_philippines_tiny_bert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|waray_philippines_tiny_bert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|109.5 MB| + +## References + +https://huggingface.co/lizaboiarchuk/war-tiny-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-22_languages_bert_base_cased_en.md b/docs/_posts/ahmedlone127/2023-10-25-22_languages_bert_base_cased_en.md new file mode 100644 index 00000000000000..b4110c4c8f24bb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-22_languages_bert_base_cased_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 22_languages_bert_base_cased BertForSequenceClassification from SharanSMenon +author: John Snow Labs +name: 22_languages_bert_base_cased +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`22_languages_bert_base_cased` is a English model originally trained by SharanSMenon. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/22_languages_bert_base_cased_en_5.1.4_3.4_1698247449271.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/22_languages_bert_base_cased_en_5.1.4_3.4_1698247449271.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("22_languages_bert_base_cased","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("22_languages_bert_base_cased","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|22_languages_bert_base_cased| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/SharanSMenon/22-languages-bert-base-cased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_0_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_0_en.md new file mode 100644 index 00000000000000..008224d969811c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_0_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_0 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_0 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_0` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_0_en_5.1.4_3.4_1698253166052.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_0_en_5.1.4_3.4_1698253166052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_0","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_0","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_0| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_10_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_10_en.md new file mode 100644 index 00000000000000..03d248f8f78ec3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_10_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_10 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_10 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_10` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_10_en_5.1.4_3.4_1698261608790.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_10_en_5.1.4_3.4_1698261608790.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_10","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_10","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_10| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_11_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_11_en.md new file mode 100644 index 00000000000000..a0fba4985e93b5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_11_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_11 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_11 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_11` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_11_en_5.1.4_3.4_1698262418067.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_11_en_5.1.4_3.4_1698262418067.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_11","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_11","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_11| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-11 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_12_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_12_en.md new file mode 100644 index 00000000000000..9e35e262e1a52a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_12_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_12 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_12 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_12` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_12_en_5.1.4_3.4_1698263175775.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_12_en_5.1.4_3.4_1698263175775.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_12","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_12","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_12| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-12 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_13_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_13_en.md new file mode 100644 index 00000000000000..c3fe1d17ae549b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_13_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_13 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_13 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_13` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_13_en_5.1.4_3.4_1698263891012.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_13_en_5.1.4_3.4_1698263891012.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_13","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_13","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_13| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-13 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_14_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_14_en.md new file mode 100644 index 00000000000000..4cb602e0cfec9b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_14_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_14 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_14 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_14` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_14_en_5.1.4_3.4_1698264650124.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_14_en_5.1.4_3.4_1698264650124.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_14","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_14","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_14| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-14 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_15_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_15_en.md new file mode 100644 index 00000000000000..c415519bdb500c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_15_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_15 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_15 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_15` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_15_en_5.1.4_3.4_1698265490438.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_15_en_5.1.4_3.4_1698265490438.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_15","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_15","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_15| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-15 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_16_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_16_en.md new file mode 100644 index 00000000000000..c5a039c5e644c2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_16_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_16 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_16 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_16` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_16_en_5.1.4_3.4_1698266482423.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_16_en_5.1.4_3.4_1698266482423.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_16","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_16","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_16| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-16 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_17_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_17_en.md new file mode 100644 index 00000000000000..2d0e48b0d26d75 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_17_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_17 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_17 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_17` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_17_en_5.1.4_3.4_1698267365486.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_17_en_5.1.4_3.4_1698267365486.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_17","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_17","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_17| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-17 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_18_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_18_en.md new file mode 100644 index 00000000000000..403105fe96451a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_18_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_18 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_18 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_18` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_18_en_5.1.4_3.4_1698268241788.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_18_en_5.1.4_3.4_1698268241788.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_18","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_18","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_18| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-18 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_19_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_19_en.md new file mode 100644 index 00000000000000..6d93adb9d6bdd1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_19_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_19 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_19 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_19` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_19_en_5.1.4_3.4_1698269068968.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_19_en_5.1.4_3.4_1698269068968.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_19","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_19","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_19| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-19 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_1_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_1_en.md new file mode 100644 index 00000000000000..56218223570386 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_1_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_1 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_1 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_1` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_1_en_5.1.4_3.4_1698253969671.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_1_en_5.1.4_3.4_1698253969671.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_1","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_1","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_20_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_20_en.md new file mode 100644 index 00000000000000..7c435c5b86f1fb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_20_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_20 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_20 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_20` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_20_en_5.1.4_3.4_1698269802842.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_20_en_5.1.4_3.4_1698269802842.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_20","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_20","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_20| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-20 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_21_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_21_en.md new file mode 100644 index 00000000000000..9e9e2d5658bfcf --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_21_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_21 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_21 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_21` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_21_en_5.1.4_3.4_1698270716210.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_21_en_5.1.4_3.4_1698270716210.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_21","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_21","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_21| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-21 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_22_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_22_en.md new file mode 100644 index 00000000000000..6c71e3e098ae30 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_22_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_22 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_22 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_22` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_22_en_5.1.4_3.4_1698271464883.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_22_en_5.1.4_3.4_1698271464883.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_22","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_22","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_22| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-22 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_23_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_23_en.md new file mode 100644 index 00000000000000..43bca9fa97e0c5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_23_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_23 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_23 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_23` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_23_en_5.1.4_3.4_1698272325215.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_23_en_5.1.4_3.4_1698272325215.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_23","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_23","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_23| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-23 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_24_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_24_en.md new file mode 100644 index 00000000000000..b44f0b890f0f40 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_24_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_24 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_24 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_24` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_24_en_5.1.4_3.4_1698273091954.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_24_en_5.1.4_3.4_1698273091954.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_24","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_24","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_24| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-24 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_25_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_25_en.md new file mode 100644 index 00000000000000..c594762801ec84 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_25_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_25 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_25 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_25` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_25_en_5.1.4_3.4_1698274055819.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_25_en_5.1.4_3.4_1698274055819.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_25","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_25","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_25| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-25 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_26_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_26_en.md new file mode 100644 index 00000000000000..374be3e244ee7c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_26_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_26 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_26 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_26` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_26_en_5.1.4_3.4_1698274824916.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_26_en_5.1.4_3.4_1698274824916.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_26","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_26","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_26| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-26 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_27_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_27_en.md new file mode 100644 index 00000000000000..a866bff8c59cb8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_27_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_27 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_27 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_27` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_27_en_5.1.4_3.4_1698275884617.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_27_en_5.1.4_3.4_1698275884617.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_27","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_27","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_27| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-27 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_28_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_28_en.md new file mode 100644 index 00000000000000..7e6013de5b3078 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_28_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_28 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_28 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_28` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_28_en_5.1.4_3.4_1698276743401.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_28_en_5.1.4_3.4_1698276743401.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_28","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_28","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_28| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-28 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_29_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_29_en.md new file mode 100644 index 00000000000000..2327a5ca943659 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_29_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_29 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_29 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_29` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_29_en_5.1.4_3.4_1698277388273.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_29_en_5.1.4_3.4_1698277388273.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_29","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_29","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_29| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-29 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_2_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_2_en.md new file mode 100644 index 00000000000000..ed93540bf488f3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_2 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_2` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_2_en_5.1.4_3.4_1698254514952.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_2_en_5.1.4_3.4_1698254514952.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_30_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_30_en.md new file mode 100644 index 00000000000000..82db308ee89551 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_30_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_30 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_30 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_30` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_30_en_5.1.4_3.4_1698278240367.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_30_en_5.1.4_3.4_1698278240367.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_30","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_30","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_30| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-30 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_3_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_3_en.md new file mode 100644 index 00000000000000..077ce9c4048a57 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_3_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_3 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_3 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_3` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_3_en_5.1.4_3.4_1698255296378.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_3_en_5.1.4_3.4_1698255296378.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_3","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_3","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_3| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_4_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_4_en.md new file mode 100644 index 00000000000000..e47453def8355c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_4_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_4 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_4 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_4` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_4_en_5.1.4_3.4_1698256192915.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_4_en_5.1.4_3.4_1698256192915.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_4","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_4","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_4| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_5_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_5_en.md new file mode 100644 index 00000000000000..31b621cbb49941 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_5_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_5 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_5 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_5` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_5_en_5.1.4_3.4_1698257229791.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_5_en_5.1.4_3.4_1698257229791.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_5","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_5","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_5| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_6_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_6_en.md new file mode 100644 index 00000000000000..b6fca803be6766 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_6_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_6 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_6 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_6` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_6_en_5.1.4_3.4_1698258140211.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_6_en_5.1.4_3.4_1698258140211.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_6","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_6","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_6| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_7_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_7_en.md new file mode 100644 index 00000000000000..7db57fb483e055 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_7_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_7 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_7 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_7` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_7_en_5.1.4_3.4_1698258839246.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_7_en_5.1.4_3.4_1698258839246.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_7","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_7","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_7| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-7 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_8_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_8_en.md new file mode 100644 index 00000000000000..e748bc4f7c0edc --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_8_en_5.1.4_3.4_1698259697258.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_8_en_5.1.4_3.4_1698259697258.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_9_en.md b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_9_en.md new file mode 100644 index 00000000000000..38a4cc641d9614 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-6ep_bert_ft_cola_9_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_9 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_9 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_9` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_9_en_5.1.4_3.4_1698260656905.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_9_en_5.1.4_3.4_1698260656905.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_9","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_9","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_9| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-9 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-a01_suicide_bert_huggingface_finetune_en.md b/docs/_posts/ahmedlone127/2023-10-25-a01_suicide_bert_huggingface_finetune_en.md new file mode 100644 index 00000000000000..b6f2767b0f2302 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-a01_suicide_bert_huggingface_finetune_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English a01_suicide_bert_huggingface_finetune BertForSequenceClassification from Ariffnaz +author: John Snow Labs +name: a01_suicide_bert_huggingface_finetune +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`a01_suicide_bert_huggingface_finetune` is a English model originally trained by Ariffnaz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/a01_suicide_bert_huggingface_finetune_en_5.1.4_3.4_1698231600777.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/a01_suicide_bert_huggingface_finetune_en_5.1.4_3.4_1698231600777.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("a01_suicide_bert_huggingface_finetune","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("a01_suicide_bert_huggingface_finetune","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|a01_suicide_bert_huggingface_finetune| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Ariffnaz/a01-suicide-bert-huggingface-finetune \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-a02_suicide_bert_huggingface_finetune_en.md b/docs/_posts/ahmedlone127/2023-10-25-a02_suicide_bert_huggingface_finetune_en.md new file mode 100644 index 00000000000000..257a39a4621e78 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-a02_suicide_bert_huggingface_finetune_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English a02_suicide_bert_huggingface_finetune BertForSequenceClassification from Ariffnaz +author: John Snow Labs +name: a02_suicide_bert_huggingface_finetune +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`a02_suicide_bert_huggingface_finetune` is a English model originally trained by Ariffnaz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/a02_suicide_bert_huggingface_finetune_en_5.1.4_3.4_1698233704009.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/a02_suicide_bert_huggingface_finetune_en_5.1.4_3.4_1698233704009.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("a02_suicide_bert_huggingface_finetune","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("a02_suicide_bert_huggingface_finetune","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|a02_suicide_bert_huggingface_finetune| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Ariffnaz/a02-suicide-bert-huggingface-finetune \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-adept_bert_en.md b/docs/_posts/ahmedlone127/2023-10-25-adept_bert_en.md new file mode 100644 index 00000000000000..4e5538cf0663c8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-adept_bert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English adept_bert BertForSequenceClassification from veronica320 +author: John Snow Labs +name: adept_bert +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adept_bert` is a English model originally trained by veronica320. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adept_bert_en_5.1.4_3.4_1698198567758.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adept_bert_en_5.1.4_3.4_1698198567758.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("adept_bert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("adept_bert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|adept_bert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/veronica320/ADEPT_bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-adept_bert_l_en.md b/docs/_posts/ahmedlone127/2023-10-25-adept_bert_l_en.md new file mode 100644 index 00000000000000..7570ffe0101a84 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-adept_bert_l_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English adept_bert_l BertForSequenceClassification from veronica320 +author: John Snow Labs +name: adept_bert_l +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`adept_bert_l` is a English model originally trained by veronica320. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/adept_bert_l_en_5.1.4_3.4_1698198952955.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/adept_bert_l_en_5.1.4_3.4_1698198952955.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("adept_bert_l","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("adept_bert_l","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|adept_bert_l| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/veronica320/ADEPT_bert-l \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-ag_news_bert_base_uncased_en.md b/docs/_posts/ahmedlone127/2023-10-25-ag_news_bert_base_uncased_en.md new file mode 100644 index 00000000000000..716d441fbee0e2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-ag_news_bert_base_uncased_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English ag_news_bert_base_uncased BertForSequenceClassification from Kyle1668 +author: John Snow Labs +name: ag_news_bert_base_uncased +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ag_news_bert_base_uncased` is a English model originally trained by Kyle1668. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ag_news_bert_base_uncased_en_5.1.4_3.4_1698221722413.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ag_news_bert_base_uncased_en_5.1.4_3.4_1698221722413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("ag_news_bert_base_uncased","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("ag_news_bert_base_uncased","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ag_news_bert_base_uncased| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Kyle1668/ag-news-bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-autotrain_bert_nlp_3450894022_en.md b/docs/_posts/ahmedlone127/2023-10-25-autotrain_bert_nlp_3450894022_en.md new file mode 100644 index 00000000000000..7ca4cfc5b5b69f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-autotrain_bert_nlp_3450894022_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English autotrain_bert_nlp_3450894022 BertForSequenceClassification from hanselgm +author: John Snow Labs +name: autotrain_bert_nlp_3450894022 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_bert_nlp_3450894022` is a English model originally trained by hanselgm. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_bert_nlp_3450894022_en_5.1.4_3.4_1698207136443.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_bert_nlp_3450894022_en_5.1.4_3.4_1698207136443.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("autotrain_bert_nlp_3450894022","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("autotrain_bert_nlp_3450894022","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_bert_nlp_3450894022| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/hanselgm/autotrain-bert-nlp-3450894022 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-autotrain_bert_wikipedia_sst_2_1034235513_en.md b/docs/_posts/ahmedlone127/2023-10-25-autotrain_bert_wikipedia_sst_2_1034235513_en.md new file mode 100644 index 00000000000000..29142f1ea13ac5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-autotrain_bert_wikipedia_sst_2_1034235513_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English autotrain_bert_wikipedia_sst_2_1034235513 BertForSequenceClassification from deepesh0x +author: John Snow Labs +name: autotrain_bert_wikipedia_sst_2_1034235513 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_bert_wikipedia_sst_2_1034235513` is a English model originally trained by deepesh0x. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_bert_wikipedia_sst_2_1034235513_en_5.1.4_3.4_1698212254160.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_bert_wikipedia_sst_2_1034235513_en_5.1.4_3.4_1698212254160.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("autotrain_bert_wikipedia_sst_2_1034235513","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("autotrain_bert_wikipedia_sst_2_1034235513","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_bert_wikipedia_sst_2_1034235513| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/deepesh0x/autotrain-bert_wikipedia_sst_2-1034235513 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-autotrain_test_4_macbert_1071837613_en.md b/docs/_posts/ahmedlone127/2023-10-25-autotrain_test_4_macbert_1071837613_en.md new file mode 100644 index 00000000000000..28e8165beadbe7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-autotrain_test_4_macbert_1071837613_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English autotrain_test_4_macbert_1071837613 BertForSequenceClassification from Luojike +author: John Snow Labs +name: autotrain_test_4_macbert_1071837613 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autotrain_test_4_macbert_1071837613` is a English model originally trained by Luojike. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autotrain_test_4_macbert_1071837613_en_5.1.4_3.4_1698267335416.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autotrain_test_4_macbert_1071837613_en_5.1.4_3.4_1698267335416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("autotrain_test_4_macbert_1071837613","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("autotrain_test_4_macbert_1071837613","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autotrain_test_4_macbert_1071837613| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/Luojike/autotrain-test-4-macbert-1071837613 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-backdoored_bert_finetuned_sst2_en.md b/docs/_posts/ahmedlone127/2023-10-25-backdoored_bert_finetuned_sst2_en.md new file mode 100644 index 00000000000000..e9aa17d4cb6602 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-backdoored_bert_finetuned_sst2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English backdoored_bert_finetuned_sst2 BertForSequenceClassification from grbagwe +author: John Snow Labs +name: backdoored_bert_finetuned_sst2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`backdoored_bert_finetuned_sst2` is a English model originally trained by grbagwe. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/backdoored_bert_finetuned_sst2_en_5.1.4_3.4_1698202142496.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/backdoored_bert_finetuned_sst2_en_5.1.4_3.4_1698202142496.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("backdoored_bert_finetuned_sst2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("backdoored_bert_finetuned_sst2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|backdoored_bert_finetuned_sst2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/grbagwe/backdoored_bert-finetuned-sst2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bangla_fake_news_mbert_en.md b/docs/_posts/ahmedlone127/2023-10-25-bangla_fake_news_mbert_en.md new file mode 100644 index 00000000000000..71c43ad7b09081 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bangla_fake_news_mbert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bangla_fake_news_mbert BertForSequenceClassification from Tahsin-Mayeesha +author: John Snow Labs +name: bangla_fake_news_mbert +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bangla_fake_news_mbert` is a English model originally trained by Tahsin-Mayeesha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bangla_fake_news_mbert_en_5.1.4_3.4_1698250864297.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bangla_fake_news_mbert_en_5.1.4_3.4_1698250864297.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bangla_fake_news_mbert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bangla_fake_news_mbert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bangla_fake_news_mbert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|667.3 MB| + +## References + +https://huggingface.co/Tahsin-Mayeesha/bangla-fake-news-mbert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-baseline_bert_base_cased_epoch3_batch4_lr2e_05_w0_01_en.md b/docs/_posts/ahmedlone127/2023-10-25-baseline_bert_base_cased_epoch3_batch4_lr2e_05_w0_01_en.md new file mode 100644 index 00000000000000..4df20a4bbda04e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-baseline_bert_base_cased_epoch3_batch4_lr2e_05_w0_01_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English baseline_bert_base_cased_epoch3_batch4_lr2e_05_w0_01 BertForSequenceClassification from JerryYanJiang +author: John Snow Labs +name: baseline_bert_base_cased_epoch3_batch4_lr2e_05_w0_01 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`baseline_bert_base_cased_epoch3_batch4_lr2e_05_w0_01` is a English model originally trained by JerryYanJiang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/baseline_bert_base_cased_epoch3_batch4_lr2e_05_w0_01_en_5.1.4_3.4_1698214827245.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/baseline_bert_base_cased_epoch3_batch4_lr2e_05_w0_01_en_5.1.4_3.4_1698214827245.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("baseline_bert_base_cased_epoch3_batch4_lr2e_05_w0_01","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("baseline_bert_base_cased_epoch3_batch4_lr2e_05_w0_01","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|baseline_bert_base_cased_epoch3_batch4_lr2e_05_w0_01| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/JerryYanJiang/baseline_bert-base-cased_epoch3_batch4_lr2e-05_w0.01 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-baseline_bert_large_cased_epoch3_batch4_lr2e_05_w0_01_en.md b/docs/_posts/ahmedlone127/2023-10-25-baseline_bert_large_cased_epoch3_batch4_lr2e_05_w0_01_en.md new file mode 100644 index 00000000000000..2f38d8481bb9a1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-baseline_bert_large_cased_epoch3_batch4_lr2e_05_w0_01_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English baseline_bert_large_cased_epoch3_batch4_lr2e_05_w0_01 BertForSequenceClassification from JerryYanJiang +author: John Snow Labs +name: baseline_bert_large_cased_epoch3_batch4_lr2e_05_w0_01 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`baseline_bert_large_cased_epoch3_batch4_lr2e_05_w0_01` is a English model originally trained by JerryYanJiang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/baseline_bert_large_cased_epoch3_batch4_lr2e_05_w0_01_en_5.1.4_3.4_1698217405966.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/baseline_bert_large_cased_epoch3_batch4_lr2e_05_w0_01_en_5.1.4_3.4_1698217405966.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("baseline_bert_large_cased_epoch3_batch4_lr2e_05_w0_01","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("baseline_bert_large_cased_epoch3_batch4_lr2e_05_w0_01","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|baseline_bert_large_cased_epoch3_batch4_lr2e_05_w0_01| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/JerryYanJiang/baseline_bert-large-cased_epoch3_batch4_lr2e-05_w0.01 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_clean_with_unclean_valid_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_clean_with_unclean_valid_en.md new file mode 100644 index 00000000000000..0dbeba1656cf73 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_clean_with_unclean_valid_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_asian_clean_with_unclean_valid BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_asian_clean_with_unclean_valid +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_asian_clean_with_unclean_valid` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asian_clean_with_unclean_valid_en_5.1.4_3.4_1698194312263.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asian_clean_with_unclean_valid_en_5.1.4_3.4_1698194312263.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asian_clean_with_unclean_valid","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asian_clean_with_unclean_valid","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_asian_clean_with_unclean_valid| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-asian-clean-with-unclean-valid \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_freeze_12_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_freeze_12_en.md new file mode 100644 index 00000000000000..1e898a08cd27ae --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_freeze_12_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_asian_unclean_freeze_12 BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_asian_unclean_freeze_12 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_asian_unclean_freeze_12` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asian_unclean_freeze_12_en_5.1.4_3.4_1698194504882.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asian_unclean_freeze_12_en_5.1.4_3.4_1698194504882.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asian_unclean_freeze_12","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asian_unclean_freeze_12","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_asian_unclean_freeze_12| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-asian-unclean-freeze-12 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_freeze_4_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_freeze_4_en.md new file mode 100644 index 00000000000000..b8b33152de5343 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_freeze_4_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_asian_unclean_freeze_4 BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_asian_unclean_freeze_4 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_asian_unclean_freeze_4` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asian_unclean_freeze_4_en_5.1.4_3.4_1698194749054.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asian_unclean_freeze_4_en_5.1.4_3.4_1698194749054.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asian_unclean_freeze_4","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asian_unclean_freeze_4","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_asian_unclean_freeze_4| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-asian-unclean-freeze-4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_freeze_8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_freeze_8_en.md new file mode 100644 index 00000000000000..1cf67c3bb9674e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_freeze_8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_asian_unclean_freeze_8 BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_asian_unclean_freeze_8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_asian_unclean_freeze_8` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asian_unclean_freeze_8_en_5.1.4_3.4_1698194950560.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asian_unclean_freeze_8_en_5.1.4_3.4_1698194950560.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asian_unclean_freeze_8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asian_unclean_freeze_8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_asian_unclean_freeze_8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-asian-unclean-freeze-8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_slanted_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_slanted_en.md new file mode 100644 index 00000000000000..51d2b4b58d6e1f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_slanted_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_asian_unclean_slanted BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_asian_unclean_slanted +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_asian_unclean_slanted` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asian_unclean_slanted_en_5.1.4_3.4_1698195152306.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asian_unclean_slanted_en_5.1.4_3.4_1698195152306.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asian_unclean_slanted","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asian_unclean_slanted","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_asian_unclean_slanted| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-asian-unclean-slanted \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_warmup_100_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_warmup_100_en.md new file mode 100644 index 00000000000000..27a80a35a9cb64 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_warmup_100_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_asian_unclean_warmup_100 BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_asian_unclean_warmup_100 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_asian_unclean_warmup_100` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asian_unclean_warmup_100_en_5.1.4_3.4_1698195329133.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asian_unclean_warmup_100_en_5.1.4_3.4_1698195329133.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asian_unclean_warmup_100","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asian_unclean_warmup_100","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_asian_unclean_warmup_100| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-asian-unclean-warmup-100 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_warmup_25_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_warmup_25_en.md new file mode 100644 index 00000000000000..cc1f5624144604 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_warmup_25_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_asian_unclean_warmup_25 BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_asian_unclean_warmup_25 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_asian_unclean_warmup_25` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asian_unclean_warmup_25_en_5.1.4_3.4_1698195519197.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asian_unclean_warmup_25_en_5.1.4_3.4_1698195519197.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asian_unclean_warmup_25","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asian_unclean_warmup_25","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_asian_unclean_warmup_25| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-asian-unclean-warmup-25 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_warmup_50_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_warmup_50_en.md new file mode 100644 index 00000000000000..cd3ee8a625278c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_warmup_50_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_asian_unclean_warmup_50 BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_asian_unclean_warmup_50 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_asian_unclean_warmup_50` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asian_unclean_warmup_50_en_5.1.4_3.4_1698195712500.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asian_unclean_warmup_50_en_5.1.4_3.4_1698195712500.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asian_unclean_warmup_50","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asian_unclean_warmup_50","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_asian_unclean_warmup_50| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-asian-unclean-warmup-50 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_warmup_75_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_warmup_75_en.md new file mode 100644 index 00000000000000..52abcfc9a23a56 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_warmup_75_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_asian_unclean_warmup_75 BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_asian_unclean_warmup_75 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_asian_unclean_warmup_75` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asian_unclean_warmup_75_en_5.1.4_3.4_1698195894104.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asian_unclean_warmup_75_en_5.1.4_3.4_1698195894104.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asian_unclean_warmup_75","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asian_unclean_warmup_75","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_asian_unclean_warmup_75| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-asian-unclean-warmup-75 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_with_clean_valid_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_with_clean_valid_en.md new file mode 100644 index 00000000000000..33f48a40e38792 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asian_unclean_with_clean_valid_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_asian_unclean_with_clean_valid BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_asian_unclean_with_clean_valid +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_asian_unclean_with_clean_valid` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asian_unclean_with_clean_valid_en_5.1.4_3.4_1698196100057.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asian_unclean_with_clean_valid_en_5.1.4_3.4_1698196100057.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asian_unclean_with_clean_valid","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asian_unclean_with_clean_valid","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_asian_unclean_with_clean_valid| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-asian-unclean-with-clean-valid \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asonam_clean_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asonam_clean_en.md new file mode 100644 index 00000000000000..d9eea287cca618 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asonam_clean_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_asonam_clean BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_asonam_clean +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_asonam_clean` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asonam_clean_en_5.1.4_3.4_1698196311214.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asonam_clean_en_5.1.4_3.4_1698196311214.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asonam_clean","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asonam_clean","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_asonam_clean| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-asonam-clean \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asonam_unclean_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asonam_unclean_en.md new file mode 100644 index 00000000000000..c544c4e971340d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_asonam_unclean_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_asonam_unclean BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_asonam_unclean +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_asonam_unclean` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asonam_unclean_en_5.1.4_3.4_1698196487339.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_asonam_unclean_en_5.1.4_3.4_1698196487339.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asonam_unclean","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_asonam_unclean","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_asonam_unclean| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-asonam-unclean \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_concat_clean_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_concat_clean_en.md new file mode 100644 index 00000000000000..963151a86f9bad --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_concat_clean_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_concat_clean BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_concat_clean +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_concat_clean` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_concat_clean_en_5.1.4_3.4_1698196932737.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_concat_clean_en_5.1.4_3.4_1698196932737.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_concat_clean","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_concat_clean","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_concat_clean| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-concat-clean \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_concat_clean_with_unclean_valid_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_concat_clean_with_unclean_valid_en.md new file mode 100644 index 00000000000000..c9db310a770e07 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_concat_clean_with_unclean_valid_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_concat_clean_with_unclean_valid BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_concat_clean_with_unclean_valid +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_concat_clean_with_unclean_valid` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_concat_clean_with_unclean_valid_en_5.1.4_3.4_1698196715996.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_concat_clean_with_unclean_valid_en_5.1.4_3.4_1698196715996.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_concat_clean_with_unclean_valid","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_concat_clean_with_unclean_valid","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_concat_clean_with_unclean_valid| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-concat-clean-with-unclean-valid \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_concat_unclean_discriminate_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_concat_unclean_discriminate_en.md new file mode 100644 index 00000000000000..21bddd882648ec --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_concat_unclean_discriminate_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_concat_unclean_discriminate BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_concat_unclean_discriminate +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_concat_unclean_discriminate` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_concat_unclean_discriminate_en_5.1.4_3.4_1698197129523.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_concat_unclean_discriminate_en_5.1.4_3.4_1698197129523.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_concat_unclean_discriminate","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_concat_unclean_discriminate","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_concat_unclean_discriminate| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-concat-unclean-discriminate \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_concat_unclean_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_concat_unclean_en.md new file mode 100644 index 00000000000000..7ed9a07bae010d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_concat_unclean_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_concat_unclean BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_concat_unclean +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_concat_unclean` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_concat_unclean_en_5.1.4_3.4_1698197549664.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_concat_unclean_en_5.1.4_3.4_1698197549664.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_concat_unclean","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_concat_unclean","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_concat_unclean| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-concat-unclean \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_concat_unclean_with_clean_valid_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_concat_unclean_with_clean_valid_en.md new file mode 100644 index 00000000000000..e6ec588d713cc7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_concat_unclean_with_clean_valid_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_concat_unclean_with_clean_valid BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_concat_unclean_with_clean_valid +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_concat_unclean_with_clean_valid` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_concat_unclean_with_clean_valid_en_5.1.4_3.4_1698197352114.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_concat_unclean_with_clean_valid_en_5.1.4_3.4_1698197352114.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_concat_unclean_with_clean_valid","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_concat_unclean_with_clean_valid","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_concat_unclean_with_clean_valid| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-concat-unclean-with-clean-valid \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_en.md new file mode 100644 index 00000000000000..f0a3a256941894 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_self_clean BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_self_clean +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_self_clean` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_clean_en_5.1.4_3.4_1698199798192.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_clean_en_5.1.4_3.4_1698199798192.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_clean","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_clean","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_self_clean| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-self-clean \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_discriminate_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_discriminate_en.md new file mode 100644 index 00000000000000..f3598c25edf591 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_discriminate_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_self_clean_small_discriminate BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_self_clean_small_discriminate +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_self_clean_small_discriminate` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_clean_small_discriminate_en_5.1.4_3.4_1698197737729.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_clean_small_discriminate_en_5.1.4_3.4_1698197737729.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_clean_small_discriminate","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_clean_small_discriminate","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_self_clean_small_discriminate| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-self-clean-small-discriminate \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_en.md new file mode 100644 index 00000000000000..11234c2008dc85 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_self_clean_small BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_self_clean_small +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_self_clean_small` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_clean_small_en_5.1.4_3.4_1698199418472.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_clean_small_en_5.1.4_3.4_1698199418472.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_clean_small","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_clean_small","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_self_clean_small| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-self-clean-small \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_epoch5_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_epoch5_en.md new file mode 100644 index 00000000000000..b742b5a6037449 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_epoch5_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_self_clean_small_epoch5 BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_self_clean_small_epoch5 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_self_clean_small_epoch5` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_clean_small_epoch5_en_5.1.4_3.4_1698198383845.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_clean_small_epoch5_en_5.1.4_3.4_1698198383845.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_clean_small_epoch5","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_clean_small_epoch5","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_self_clean_small_epoch5| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-self-clean-small-epoch5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_epoch5_freeze4_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_epoch5_freeze4_en.md new file mode 100644 index 00000000000000..69b4e8d41b29ff --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_epoch5_freeze4_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_self_clean_small_epoch5_freeze4 BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_self_clean_small_epoch5_freeze4 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_self_clean_small_epoch5_freeze4` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_clean_small_epoch5_freeze4_en_5.1.4_3.4_1698197938358.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_clean_small_epoch5_freeze4_en_5.1.4_3.4_1698197938358.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_clean_small_epoch5_freeze4","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_clean_small_epoch5_freeze4","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_self_clean_small_epoch5_freeze4| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-self-clean-small-epoch5-freeze4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_epoch5_warmup_50_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_epoch5_warmup_50_en.md new file mode 100644 index 00000000000000..f2ac8262b57672 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_epoch5_warmup_50_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_self_clean_small_epoch5_warmup_50 BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_self_clean_small_epoch5_warmup_50 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_self_clean_small_epoch5_warmup_50` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_clean_small_epoch5_warmup_50_en_5.1.4_3.4_1698198162466.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_clean_small_epoch5_warmup_50_en_5.1.4_3.4_1698198162466.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_clean_small_epoch5_warmup_50","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_clean_small_epoch5_warmup_50","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_self_clean_small_epoch5_warmup_50| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-self-clean-small-epoch5-warmup-50 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_epoch6_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_epoch6_en.md new file mode 100644 index 00000000000000..65451f5e01d301 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_epoch6_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_self_clean_small_epoch6 BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_self_clean_small_epoch6 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_self_clean_small_epoch6` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_clean_small_epoch6_en_5.1.4_3.4_1698198646713.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_clean_small_epoch6_en_5.1.4_3.4_1698198646713.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_clean_small_epoch6","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_clean_small_epoch6","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_self_clean_small_epoch6| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-self-clean-small-epoch6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_more_epoch_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_more_epoch_en.md new file mode 100644 index 00000000000000..59fa1bd361377c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_more_epoch_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_self_clean_small_more_epoch BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_self_clean_small_more_epoch +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_self_clean_small_more_epoch` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_clean_small_more_epoch_en_5.1.4_3.4_1698198851223.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_clean_small_more_epoch_en_5.1.4_3.4_1698198851223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_clean_small_more_epoch","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_clean_small_more_epoch","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_self_clean_small_more_epoch| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-self-clean-small-more-epoch \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_warmup_100_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_warmup_100_en.md new file mode 100644 index 00000000000000..b441f7b34d02fe --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_warmup_100_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_self_clean_small_warmup_100 BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_self_clean_small_warmup_100 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_self_clean_small_warmup_100` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_clean_small_warmup_100_en_5.1.4_3.4_1698199020222.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_clean_small_warmup_100_en_5.1.4_3.4_1698199020222.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_clean_small_warmup_100","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_clean_small_warmup_100","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_self_clean_small_warmup_100| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-self-clean-small-warmup-100 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_warmup_50_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_warmup_50_en.md new file mode 100644 index 00000000000000..75ac8fbe5ac44c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_small_warmup_50_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_self_clean_small_warmup_50 BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_self_clean_small_warmup_50 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_self_clean_small_warmup_50` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_clean_small_warmup_50_en_5.1.4_3.4_1698199205772.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_clean_small_warmup_50_en_5.1.4_3.4_1698199205772.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_clean_small_warmup_50","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_clean_small_warmup_50","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_self_clean_small_warmup_50| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-self-clean-small-warmup-50 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_with_unclean_valid_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_with_unclean_valid_en.md new file mode 100644 index 00000000000000..2a2fb70e48a605 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_clean_with_unclean_valid_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_self_clean_with_unclean_valid BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_self_clean_with_unclean_valid +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_self_clean_with_unclean_valid` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_clean_with_unclean_valid_en_5.1.4_3.4_1698199619498.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_clean_with_unclean_valid_en_5.1.4_3.4_1698199619498.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_clean_with_unclean_valid","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_clean_with_unclean_valid","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_self_clean_with_unclean_valid| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-self-clean-with-unclean-valid \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_unclean_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_unclean_en.md new file mode 100644 index 00000000000000..cd7b05cf5b5a7f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_unclean_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_self_unclean BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_self_unclean +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_self_unclean` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_unclean_en_5.1.4_3.4_1698200718265.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_unclean_en_5.1.4_3.4_1698200718265.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_unclean","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_unclean","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_self_unclean| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-self-unclean \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_unclean_freeze_12_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_unclean_freeze_12_en.md new file mode 100644 index 00000000000000..95a93da85893b6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_unclean_freeze_12_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_self_unclean_freeze_12 BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_self_unclean_freeze_12 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_self_unclean_freeze_12` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_unclean_freeze_12_en_5.1.4_3.4_1698199993184.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_unclean_freeze_12_en_5.1.4_3.4_1698199993184.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_unclean_freeze_12","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_unclean_freeze_12","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_self_unclean_freeze_12| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-self-unclean-freeze-12 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_unclean_freeze_4_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_unclean_freeze_4_en.md new file mode 100644 index 00000000000000..c2c5eb4f09387c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_unclean_freeze_4_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_self_unclean_freeze_4 BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_self_unclean_freeze_4 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_self_unclean_freeze_4` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_unclean_freeze_4_en_5.1.4_3.4_1698200174510.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_unclean_freeze_4_en_5.1.4_3.4_1698200174510.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_unclean_freeze_4","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_unclean_freeze_4","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_self_unclean_freeze_4| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-self-unclean-freeze-4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_unclean_freeze_8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_unclean_freeze_8_en.md new file mode 100644 index 00000000000000..c2073cbd764639 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_unclean_freeze_8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_self_unclean_freeze_8 BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_self_unclean_freeze_8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_self_unclean_freeze_8` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_unclean_freeze_8_en_5.1.4_3.4_1698200377794.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_unclean_freeze_8_en_5.1.4_3.4_1698200377794.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_unclean_freeze_8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_unclean_freeze_8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_self_unclean_freeze_8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-self-unclean-freeze-8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_unclean_small_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_unclean_small_en.md new file mode 100644 index 00000000000000..6fd09e1abfb0f6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_unclean_small_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_self_unclean_small BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_self_unclean_small +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_self_unclean_small` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_unclean_small_en_5.1.4_3.4_1698200557344.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_unclean_small_en_5.1.4_3.4_1698200557344.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_unclean_small","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_unclean_small","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_self_unclean_small| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-self-unclean-small \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_unlean_with_clean_valid_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_unlean_with_clean_valid_en.md new file mode 100644 index 00000000000000..51f5fa8ac57d3a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_asian_hate_tweets_self_unlean_with_clean_valid_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_asian_hate_tweets_self_unlean_with_clean_valid BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_asian_hate_tweets_self_unlean_with_clean_valid +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_asian_hate_tweets_self_unlean_with_clean_valid` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_unlean_with_clean_valid_en_5.1.4_3.4_1698200938581.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_asian_hate_tweets_self_unlean_with_clean_valid_en_5.1.4_3.4_1698200938581.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_unlean_with_clean_valid","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_asian_hate_tweets_self_unlean_with_clean_valid","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_asian_hate_tweets_self_unlean_with_clean_valid| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-asian-hate-tweets-self-unlean-with-clean-valid \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabertv02_twitter_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabertv02_twitter_en.md new file mode 100644 index 00000000000000..63f1350bd99439 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabertv02_twitter_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_arabertv02_twitter BertForSequenceClassification from nouman-10 +author: John Snow Labs +name: bert_base_arabertv02_twitter +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabertv02_twitter` is a English model originally trained by nouman-10. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabertv02_twitter_en_5.1.4_3.4_1698252082816.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabertv02_twitter_en_5.1.4_3.4_1698252082816.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabertv02_twitter","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabertv02_twitter","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabertv02_twitter| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|507.3 MB| + +## References + +https://huggingface.co/nouman-10/bert-base-arabertv02-twitter \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabertv22a_preprocessed_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabertv22a_preprocessed_en.md new file mode 100644 index 00000000000000..503e8d15dcff61 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabertv22a_preprocessed_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_arabertv22a_preprocessed BertForSequenceClassification from Jehadoumer +author: John Snow Labs +name: bert_base_arabertv22a_preprocessed +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabertv22a_preprocessed` is a English model originally trained by Jehadoumer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabertv22a_preprocessed_en_5.1.4_3.4_1698248197330.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabertv22a_preprocessed_en_5.1.4_3.4_1698248197330.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabertv22a_preprocessed","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabertv22a_preprocessed","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabertv22a_preprocessed| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|507.1 MB| + +## References + +https://huggingface.co/Jehadoumer/bert-base-arabertv22a-preprocessed \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabertv2_finetuned_emotion_33_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabertv2_finetuned_emotion_33_en.md new file mode 100644 index 00000000000000..518f157f61b853 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabertv2_finetuned_emotion_33_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_arabertv2_finetuned_emotion_33 BertForSequenceClassification from MahaJar +author: John Snow Labs +name: bert_base_arabertv2_finetuned_emotion_33 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabertv2_finetuned_emotion_33` is a English model originally trained by MahaJar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabertv2_finetuned_emotion_33_en_5.1.4_3.4_1698202367716.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabertv2_finetuned_emotion_33_en_5.1.4_3.4_1698202367716.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabertv2_finetuned_emotion_33","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabertv2_finetuned_emotion_33","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabertv2_finetuned_emotion_33| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|507.1 MB| + +## References + +https://huggingface.co/MahaJar/bert-base-arabertv2-finetuned-emotion_33 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabertv2_finetuned_emotion_3_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabertv2_finetuned_emotion_3_en.md new file mode 100644 index 00000000000000..e916b5a1bbb612 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabertv2_finetuned_emotion_3_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_arabertv2_finetuned_emotion_3 BertForSequenceClassification from MahaJar +author: John Snow Labs +name: bert_base_arabertv2_finetuned_emotion_3 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabertv2_finetuned_emotion_3` is a English model originally trained by MahaJar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabertv2_finetuned_emotion_3_en_5.1.4_3.4_1698202581940.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabertv2_finetuned_emotion_3_en_5.1.4_3.4_1698202581940.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabertv2_finetuned_emotion_3","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabertv2_finetuned_emotion_3","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabertv2_finetuned_emotion_3| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|507.1 MB| + +## References + +https://huggingface.co/MahaJar/bert-base-arabertv2-finetuned-emotion_3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabertv2_jehadoumer_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabertv2_jehadoumer_en.md new file mode 100644 index 00000000000000..aff780285b9835 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabertv2_jehadoumer_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_arabertv2_jehadoumer BertForSequenceClassification from Jehadoumer +author: John Snow Labs +name: bert_base_arabertv2_jehadoumer +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabertv2_jehadoumer` is a English model originally trained by Jehadoumer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabertv2_jehadoumer_en_5.1.4_3.4_1698247360873.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabertv2_jehadoumer_en_5.1.4_3.4_1698247360873.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabertv2_jehadoumer","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabertv2_jehadoumer","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabertv2_jehadoumer| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|507.1 MB| + +## References + +https://huggingface.co/Jehadoumer/bert-base-arabertv2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabertv2_nouman_10_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabertv2_nouman_10_en.md new file mode 100644 index 00000000000000..2c815623cac192 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabertv2_nouman_10_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_arabertv2_nouman_10 BertForSequenceClassification from nouman-10 +author: John Snow Labs +name: bert_base_arabertv2_nouman_10 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabertv2_nouman_10` is a English model originally trained by nouman-10. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabertv2_nouman_10_en_5.1.4_3.4_1698249224530.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabertv2_nouman_10_en_5.1.4_3.4_1698249224530.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabertv2_nouman_10","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabertv2_nouman_10","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabertv2_nouman_10| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|507.1 MB| + +## References + +https://huggingface.co/nouman-10/bert-base-arabertv2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabertv2test_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabertv2test_en.md new file mode 100644 index 00000000000000..8d621abac5d519 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabertv2test_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_arabertv2test BertForSequenceClassification from nouman-10 +author: John Snow Labs +name: bert_base_arabertv2test +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabertv2test` is a English model originally trained by nouman-10. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabertv2test_en_5.1.4_3.4_1698252993807.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabertv2test_en_5.1.4_3.4_1698252993807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabertv2test","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabertv2test","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabertv2test| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|507.1 MB| + +## References + +https://huggingface.co/nouman-10/bert-base-arabertv2test \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabic_camelbert_msa_finetuned_arabic_dialect_identification_model_1_ar.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabic_camelbert_msa_finetuned_arabic_dialect_identification_model_1_ar.md new file mode 100644 index 00000000000000..9e7c77824e37aa --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabic_camelbert_msa_finetuned_arabic_dialect_identification_model_1_ar.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Arabic bert_base_arabic_camelbert_msa_finetuned_arabic_dialect_identification_model_1 BertForSequenceClassification from Abdelrahman-Rezk +author: John Snow Labs +name: bert_base_arabic_camelbert_msa_finetuned_arabic_dialect_identification_model_1 +date: 2023-10-25 +tags: [bert, ar, open_source, sequence_classification, onnx] +task: Text Classification +language: ar +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabic_camelbert_msa_finetuned_arabic_dialect_identification_model_1` is a Arabic model originally trained by Abdelrahman-Rezk. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_msa_finetuned_arabic_dialect_identification_model_1_ar_5.1.4_3.4_1698213574208.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_msa_finetuned_arabic_dialect_identification_model_1_ar_5.1.4_3.4_1698213574208.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabic_camelbert_msa_finetuned_arabic_dialect_identification_model_1","ar")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabic_camelbert_msa_finetuned_arabic_dialect_identification_model_1","ar") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabic_camelbert_msa_finetuned_arabic_dialect_identification_model_1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|ar| +|Size:|408.6 MB| + +## References + +https://huggingface.co/Abdelrahman-Rezk/bert-base-arabic-camelbert-msa-finetuned-Arabic_Dialect_Identification_model_1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_sarahadnan_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_sarahadnan_en.md new file mode 100644 index 00000000000000..32f1070e740dba --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_sarahadnan_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_sarahadnan BertForSequenceClassification from SarahAdnan +author: John Snow Labs +name: bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_sarahadnan +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_sarahadnan` is a English model originally trained by SarahAdnan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_sarahadnan_en_5.1.4_3.4_1698210534868.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_sarahadnan_en_5.1.4_3.4_1698210534868.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_sarahadnan","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_sarahadnan","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_sarahadnan| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|507.3 MB| + +## References + +https://huggingface.co/SarahAdnan/bert-base-arabic-camelbert-msa-sixteenth-xnli-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_banking77_pt2_laurie_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_banking77_pt2_laurie_en.md new file mode 100644 index 00000000000000..d4ac1250b3b35c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_banking77_pt2_laurie_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_banking77_pt2_laurie BertForSequenceClassification from Laurie +author: John Snow Labs +name: bert_base_banking77_pt2_laurie +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_banking77_pt2_laurie` is a English model originally trained by Laurie. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_laurie_en_5.1.4_3.4_1698207333851.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_laurie_en_5.1.4_3.4_1698207333851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_banking77_pt2_laurie","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_banking77_pt2_laurie","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_banking77_pt2_laurie| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/Laurie/bert-base-banking77-pt2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_banking77_pt2_shahzay_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_banking77_pt2_shahzay_en.md new file mode 100644 index 00000000000000..cde9393c012c99 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_banking77_pt2_shahzay_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_banking77_pt2_shahzay BertForSequenceClassification from Shahzay +author: John Snow Labs +name: bert_base_banking77_pt2_shahzay +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_banking77_pt2_shahzay` is a English model originally trained by Shahzay. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_shahzay_en_5.1.4_3.4_1698251201329.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_banking77_pt2_shahzay_en_5.1.4_3.4_1698251201329.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_banking77_pt2_shahzay","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_banking77_pt2_shahzay","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_banking77_pt2_shahzay| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/Shahzay/bert-base-banking77-pt2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_avg_cola_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_avg_cola_en.md new file mode 100644 index 00000000000000..bc50664366521b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_avg_cola_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_cased_avg_cola BertForSequenceClassification from TehranNLP-org +author: John Snow Labs +name: bert_base_cased_avg_cola +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_avg_cola` is a English model originally trained by TehranNLP-org. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_avg_cola_en_5.1.4_3.4_1698254382799.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_avg_cola_en_5.1.4_3.4_1698254382799.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_avg_cola","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_avg_cola","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_avg_cola| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/TehranNLP-org/bert-base-cased-avg-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_avg_mnli_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_avg_mnli_en.md new file mode 100644 index 00000000000000..21fadcd92682c8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_avg_mnli_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_cased_avg_mnli BertForSequenceClassification from TehranNLP-org +author: John Snow Labs +name: bert_base_cased_avg_mnli +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_avg_mnli` is a English model originally trained by TehranNLP-org. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_avg_mnli_en_5.1.4_3.4_1698255296405.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_avg_mnli_en_5.1.4_3.4_1698255296405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_avg_mnli","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_avg_mnli","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_avg_mnli| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/TehranNLP-org/bert-base-cased-avg-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_fake_real_2_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_fake_real_2_en.md new file mode 100644 index 00000000000000..6fdf09d0f493a6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_fake_real_2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_cased_fake_real_2 BertForSequenceClassification from VA777 +author: John Snow Labs +name: bert_base_cased_fake_real_2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_fake_real_2` is a English model originally trained by VA777. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_fake_real_2_en_5.1.4_3.4_1698252013476.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_fake_real_2_en_5.1.4_3.4_1698252013476.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_fake_real_2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_fake_real_2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_fake_real_2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/VA777/bert_base_cased_fake_real_2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_fake_real_3_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_fake_real_3_en.md new file mode 100644 index 00000000000000..0bafe338ef6e3d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_fake_real_3_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_cased_fake_real_3 BertForSequenceClassification from VA777 +author: John Snow Labs +name: bert_base_cased_fake_real_3 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_fake_real_3` is a English model originally trained by VA777. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_fake_real_3_en_5.1.4_3.4_1698252780645.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_fake_real_3_en_5.1.4_3.4_1698252780645.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_fake_real_3","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_fake_real_3","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_fake_real_3| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/VA777/bert_base_cased_fake_real_3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_fake_real_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_fake_real_en.md new file mode 100644 index 00000000000000..2fab8ccaf3e512 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_fake_real_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_cased_fake_real BertForSequenceClassification from VA777 +author: John Snow Labs +name: bert_base_cased_fake_real +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_fake_real` is a English model originally trained by VA777. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_fake_real_en_5.1.4_3.4_1698250505726.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_fake_real_en_5.1.4_3.4_1698250505726.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_fake_real","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_fake_real","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_fake_real| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.8 MB| + +## References + +https://huggingface.co/VA777/bert_base_cased_fake_real \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_finetuned_cola_sreyang_nvidia_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_finetuned_cola_sreyang_nvidia_en.md new file mode 100644 index 00000000000000..416af5ec23cb6c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_finetuned_cola_sreyang_nvidia_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_cased_finetuned_cola_sreyang_nvidia BertForSequenceClassification from SreyanG-NVIDIA +author: John Snow Labs +name: bert_base_cased_finetuned_cola_sreyang_nvidia +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_finetuned_cola_sreyang_nvidia` is a English model originally trained by SreyanG-NVIDIA. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_cola_sreyang_nvidia_en_5.1.4_3.4_1698239875860.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_cola_sreyang_nvidia_en_5.1.4_3.4_1698239875860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_finetuned_cola_sreyang_nvidia","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_finetuned_cola_sreyang_nvidia","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_finetuned_cola_sreyang_nvidia| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/SreyanG-NVIDIA/bert-base-cased-finetuned-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_finetuned_textclassification_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_finetuned_textclassification_en.md new file mode 100644 index 00000000000000..2ff305bb7cff66 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_finetuned_textclassification_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_cased_finetuned_textclassification BertForSequenceClassification from Kekelilii +author: John Snow Labs +name: bert_base_cased_finetuned_textclassification +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_finetuned_textclassification` is a English model originally trained by Kekelilii. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_textclassification_en_5.1.4_3.4_1698196500566.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_finetuned_textclassification_en_5.1.4_3.4_1698196500566.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_finetuned_textclassification","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_finetuned_textclassification","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_finetuned_textclassification| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Kekelilii/bert-base-cased_finetuned_TextClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_manifesto_2018_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_manifesto_2018_en.md new file mode 100644 index 00000000000000..6c7c333eaa5a78 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_manifesto_2018_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_cased_manifesto_2018 BertForSequenceClassification from assenmacher +author: John Snow Labs +name: bert_base_cased_manifesto_2018 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_manifesto_2018` is a English model originally trained by assenmacher. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_manifesto_2018_en_5.1.4_3.4_1698208505640.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_manifesto_2018_en_5.1.4_3.4_1698208505640.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_manifesto_2018","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_manifesto_2018","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_manifesto_2018| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/assenmacher/bert-base-cased-manifesto-2018 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_mnli_tehrannlp_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_mnli_tehrannlp_en.md new file mode 100644 index 00000000000000..b74689e0a2bc90 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_mnli_tehrannlp_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_cased_mnli_tehrannlp BertForSequenceClassification from TehranNLP +author: John Snow Labs +name: bert_base_cased_mnli_tehrannlp +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_mnli_tehrannlp` is a English model originally trained by TehranNLP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_mnli_tehrannlp_en_5.1.4_3.4_1698252780573.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_mnli_tehrannlp_en_5.1.4_3.4_1698252780573.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_mnli_tehrannlp","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_mnli_tehrannlp","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_mnli_tehrannlp| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.8 MB| + +## References + +https://huggingface.co/TehranNLP/bert-base-cased-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_resume_classification_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_resume_classification_en.md new file mode 100644 index 00000000000000..4b1ccd25f0643a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_resume_classification_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_cased_resume_classification BertForSequenceClassification from Kowshik24 +author: John Snow Labs +name: bert_base_cased_resume_classification +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_resume_classification` is a English model originally trained by Kowshik24. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_resume_classification_en_5.1.4_3.4_1698256194279.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_resume_classification_en_5.1.4_3.4_1698256194279.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_resume_classification","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_resume_classification","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_resume_classification| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Kowshik24/bert-base-cased-resume-classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_sentweet_derogatory_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_sentweet_derogatory_en.md new file mode 100644 index 00000000000000..cd24c2d33466c2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_sentweet_derogatory_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_cased_sentweet_derogatory BertForSequenceClassification from jayanta +author: John Snow Labs +name: bert_base_cased_sentweet_derogatory +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_sentweet_derogatory` is a English model originally trained by jayanta. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_sentweet_derogatory_en_5.1.4_3.4_1698195118702.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_sentweet_derogatory_en_5.1.4_3.4_1698195118702.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_sentweet_derogatory","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_sentweet_derogatory","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_sentweet_derogatory| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/jayanta/bert-base-cased-sentweet-derogatory \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_sentweet_hatespeech_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_sentweet_hatespeech_en.md new file mode 100644 index 00000000000000..3dad57b6b6dc59 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_sentweet_hatespeech_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_cased_sentweet_hatespeech BertForSequenceClassification from jayanta +author: John Snow Labs +name: bert_base_cased_sentweet_hatespeech +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_sentweet_hatespeech` is a English model originally trained by jayanta. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_sentweet_hatespeech_en_5.1.4_3.4_1698195304982.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_sentweet_hatespeech_en_5.1.4_3.4_1698195304982.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_sentweet_hatespeech","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_sentweet_hatespeech","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_sentweet_hatespeech| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/jayanta/bert-base-cased-sentweet-hatespeech \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_sentweet_profane_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_sentweet_profane_en.md new file mode 100644 index 00000000000000..8e65d2e0a03974 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_sentweet_profane_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_cased_sentweet_profane BertForSequenceClassification from jayanta +author: John Snow Labs +name: bert_base_cased_sentweet_profane +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_sentweet_profane` is a English model originally trained by jayanta. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_sentweet_profane_en_5.1.4_3.4_1698195490757.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_sentweet_profane_en_5.1.4_3.4_1698195490757.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_sentweet_profane","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_sentweet_profane","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_sentweet_profane| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/jayanta/bert-base-cased-sentweet-profane \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_sentweet_targetedinsult_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_sentweet_targetedinsult_en.md new file mode 100644 index 00000000000000..2570229e629f04 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_sentweet_targetedinsult_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_cased_sentweet_targetedinsult BertForSequenceClassification from jayanta +author: John Snow Labs +name: bert_base_cased_sentweet_targetedinsult +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_sentweet_targetedinsult` is a English model originally trained by jayanta. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_sentweet_targetedinsult_en_5.1.4_3.4_1698195678583.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_sentweet_targetedinsult_en_5.1.4_3.4_1698195678583.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_sentweet_targetedinsult","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_sentweet_targetedinsult","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_sentweet_targetedinsult| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/jayanta/bert-base-cased-sentweet-targetedinsult \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_twitter_sentiment_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_twitter_sentiment_en.md new file mode 100644 index 00000000000000..b27d37442de8c6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_cased_twitter_sentiment_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_cased_twitter_sentiment BertForSequenceClassification from Theivaprakasham +author: John Snow Labs +name: bert_base_cased_twitter_sentiment +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_cased_twitter_sentiment` is a English model originally trained by Theivaprakasham. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_cased_twitter_sentiment_en_5.1.4_3.4_1698268240508.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_cased_twitter_sentiment_en_5.1.4_3.4_1698268240508.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_twitter_sentiment","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_cased_twitter_sentiment","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_cased_twitter_sentiment| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Theivaprakasham/bert-base-cased-twitter_sentiment \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_finetuned_binary_best_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_finetuned_binary_best_en.md new file mode 100644 index 00000000000000..3c21357daf4f37 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_finetuned_binary_best_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_chinese_finetuned_binary_best BertForSequenceClassification from Raychanan +author: John Snow Labs +name: bert_base_chinese_finetuned_binary_best +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_finetuned_binary_best` is a English model originally trained by Raychanan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_binary_best_en_5.1.4_3.4_1698234417943.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_binary_best_en_5.1.4_3.4_1698234417943.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_finetuned_binary_best","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_finetuned_binary_best","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_finetuned_binary_best| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/Raychanan/bert-base-chinese-FineTuned-Binary-Best \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_finetuned_mosei1_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_finetuned_mosei1_en.md new file mode 100644 index 00000000000000..f771a1538b28bc --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_finetuned_mosei1_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_chinese_finetuned_mosei1 BertForSequenceClassification from luckydog +author: John Snow Labs +name: bert_base_chinese_finetuned_mosei1 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_finetuned_mosei1` is a English model originally trained by luckydog. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_mosei1_en_5.1.4_3.4_1698249306584.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_mosei1_en_5.1.4_3.4_1698249306584.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_finetuned_mosei1","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_finetuned_mosei1","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_finetuned_mosei1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/luckydog/bert-base-chinese-finetuned-mosei1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_finetuned_mosei_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_finetuned_mosei_en.md new file mode 100644 index 00000000000000..ecf31d4ceacfd7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_finetuned_mosei_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_chinese_finetuned_mosei BertForSequenceClassification from luckydog +author: John Snow Labs +name: bert_base_chinese_finetuned_mosei +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_finetuned_mosei` is a English model originally trained by luckydog. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_mosei_en_5.1.4_3.4_1698247667699.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuned_mosei_en_5.1.4_3.4_1698247667699.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_finetuned_mosei","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_finetuned_mosei","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_finetuned_mosei| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/luckydog/bert-base-chinese-finetuned-mosei \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1_zh.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1_zh.md new file mode 100644 index 00000000000000..bc4f8fc535c843 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1_zh.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Chinese bert_base_chinese_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1 +date: 2023-10-25 +tags: [bert, zh, open_source, sequence_classification, onnx] +task: Text Classification +language: zh +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1` is a Chinese model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1_zh_5.1.4_3.4_1698214104165.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1_zh_5.1.4_3.4_1698214104165.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1","zh")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1","zh") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|zh| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-finetuning-wallstreetcn-morning-news-market-overview-open-000001SH-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_ssec_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_ssec_en.md new file mode 100644 index 00000000000000..4fd1270ccf666e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_ssec_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_chinese_ssec BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_ssec +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_ssec` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_ssec_en_5.1.4_3.4_1698263128720.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_ssec_en_5.1.4_3.4_1698263128720.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_ssec","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_ssec","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_ssec| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-SSEC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_f1_v1_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_f1_v1_en.md new file mode 100644 index 00000000000000..4ec59ff1d51af6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_f1_v1_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_f1_v1 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_f1_v1 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_f1_v1` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_f1_v1_en_5.1.4_3.4_1698219578005.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_f1_v1_en_5.1.4_3.4_1698219578005.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_f1_v1","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_f1_v1","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_f1_v1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-wallstreetcn-morning-news-market-overview-open-SSEC-f1-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_f1_v2_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_f1_v2_en.md new file mode 100644 index 00000000000000..54e7e89e90dfaf --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_f1_v2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_f1_v2 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_f1_v2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_f1_v2` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_f1_v2_en_5.1.4_3.4_1698222739007.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_f1_v2_en_5.1.4_3.4_1698222739007.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_f1_v2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_f1_v2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_f1_v2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-wallstreetcn-morning-news-market-overview-open-SSEC-f1-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_v2_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_v2_en.md new file mode 100644 index 00000000000000..ad82bdcfa957ab --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_v2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_v2 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_v2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_v2` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_v2_en_5.1.4_3.4_1698220941999.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_v2_en_5.1.4_3.4_1698220941999.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_v2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_v2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_wallstreetcn_morning_news_market_overview_open_ssec_v2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-wallstreetcn-morning-news-market-overview-open-SSEC-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_10_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_10_en.md new file mode 100644 index 00000000000000..ce8994b8d36642 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_10_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_10 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_10 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_10` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_10_en_5.1.4_3.4_1698244428839.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_10_en_5.1.4_3.4_1698244428839.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_10","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_10","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_10| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-wallstreetcn-morning-news-market-overview-SSEC-10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_1_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_1_en.md new file mode 100644 index 00000000000000..1c9ac7f7c442c3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_1_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_1 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_1 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_1` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_1_en_5.1.4_3.4_1698231415062.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_1_en_5.1.4_3.4_1698231415062.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_1","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_1","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-wallstreetcn-morning-news-market-overview-SSEC-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_2_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_2_en.md new file mode 100644 index 00000000000000..f37188738f45cf --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_2 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_2` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_2_en_5.1.4_3.4_1698232117390.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_2_en_5.1.4_3.4_1698232117390.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-wallstreetcn-morning-news-market-overview-SSEC-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_3_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_3_en.md new file mode 100644 index 00000000000000..d68f331ff6c819 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_3_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_3 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_3 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_3` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_3_en_5.1.4_3.4_1698232786971.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_3_en_5.1.4_3.4_1698232786971.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_3","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_3","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_3| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-wallstreetcn-morning-news-market-overview-SSEC-3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_4_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_4_en.md new file mode 100644 index 00000000000000..2798c1896a7de9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_4_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_4 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_4 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_4` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_4_en_5.1.4_3.4_1698233527930.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_4_en_5.1.4_3.4_1698233527930.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_4","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_4","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_4| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-wallstreetcn-morning-news-market-overview-SSEC-4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_5_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_5_en.md new file mode 100644 index 00000000000000..f5c416b40d8d47 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_5_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_5 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_5 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_5` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_5_en_5.1.4_3.4_1698234159300.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_5_en_5.1.4_3.4_1698234159300.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_5","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_5","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_5| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-wallstreetcn-morning-news-market-overview-SSEC-5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_6_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_6_en.md new file mode 100644 index 00000000000000..1267a8354a009b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_6_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_6 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_6 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_6` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_6_en_5.1.4_3.4_1698240802038.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_6_en_5.1.4_3.4_1698240802038.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_6","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_6","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_6| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-wallstreetcn-morning-news-market-overview-SSEC-6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_7_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_7_en.md new file mode 100644 index 00000000000000..20f18fe0923de3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_7_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_7 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_7 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_7` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_7_en_5.1.4_3.4_1698241641367.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_7_en_5.1.4_3.4_1698241641367.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_7","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_7","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_7| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-wallstreetcn-morning-news-market-overview-SSEC-7 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_8_en.md new file mode 100644 index 00000000000000..4ebd1ef10fd525 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_8 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_8` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_8_en_5.1.4_3.4_1698242416129.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_8_en_5.1.4_3.4_1698242416129.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-wallstreetcn-morning-news-market-overview-SSEC-8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_9_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_9_en.md new file mode 100644 index 00000000000000..950fda31680853 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_9_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_9 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_9 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_9` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_9_en_5.1.4_3.4_1698243365653.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_9_en_5.1.4_3.4_1698243365653.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_9","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_9","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_9| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-wallstreetcn-morning-news-market-overview-SSEC-9 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v1_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v1_en.md new file mode 100644 index 00000000000000..36f48b29723b83 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v1_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v1 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v1 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v1` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v1_en_5.1.4_3.4_1698261759300.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v1_en_5.1.4_3.4_1698261759300.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v1","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v1","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-wallstreetcn-morning-news-market-overview-SSEC-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v2_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v2_en.md new file mode 100644 index 00000000000000..70041a049463c4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v2 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v2` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v2_en_5.1.4_3.4_1698262490366.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v2_en_5.1.4_3.4_1698262490366.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-wallstreetcn-morning-news-market-overview-SSEC-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v4_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v4_en.md new file mode 100644 index 00000000000000..a3ec53fb413fb5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v4_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v4 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v4 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v4` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v4_en_5.1.4_3.4_1698263835406.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v4_en_5.1.4_3.4_1698263835406.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v4","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v4","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v4| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-wallstreetcn-morning-news-market-overview-SSEC-v4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v5_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v5_en.md new file mode 100644 index 00000000000000..1362bd9eec0b79 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v5_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v5 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v5 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v5` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v5_en_5.1.4_3.4_1698264650096.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v5_en_5.1.4_3.4_1698264650096.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v5","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v5","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_chinese_wallstreetcn_morning_news_market_overview_ssec_v5| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/hw2942/bert-base-chinese-wallstreetcn-morning-news-market-overview-SSEC-v5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_dutch_cased_finetuned_dt_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_dutch_cased_finetuned_dt_en.md new file mode 100644 index 00000000000000..1ba10f1a6edf3b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_dutch_cased_finetuned_dt_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_dutch_cased_finetuned_dt BertForSequenceClassification from ArjanvD95 +author: John Snow Labs +name: bert_base_dutch_cased_finetuned_dt +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_dutch_cased_finetuned_dt` is a English model originally trained by ArjanvD95. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_dutch_cased_finetuned_dt_en_5.1.4_3.4_1698212262096.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_dutch_cased_finetuned_dt_en_5.1.4_3.4_1698212262096.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_dutch_cased_finetuned_dt","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_dutch_cased_finetuned_dt","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_dutch_cased_finetuned_dt| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.0 MB| + +## References + +https://huggingface.co/ArjanvD95/bert-base-dutch-cased-finetuned-dt \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_finetuned_emotion_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_finetuned_emotion_en.md new file mode 100644 index 00000000000000..6615f7980ee04e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_finetuned_emotion_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_finetuned_emotion BertForSequenceClassification from Woonn +author: John Snow Labs +name: bert_base_finetuned_emotion +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_finetuned_emotion` is a English model originally trained by Woonn. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_emotion_en_5.1.4_3.4_1698208768773.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_emotion_en_5.1.4_3.4_1698208768773.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_finetuned_emotion","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_finetuned_emotion","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_finetuned_emotion| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.6 MB| + +## References + +https://huggingface.co/Woonn/bert-base-finetuned-emotion \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_finetuned_nli_jihyun22_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_finetuned_nli_jihyun22_en.md new file mode 100644 index 00000000000000..a381edc0ea8b95 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_finetuned_nli_jihyun22_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_finetuned_nli_jihyun22 BertForSequenceClassification from Jihyun22 +author: John Snow Labs +name: bert_base_finetuned_nli_jihyun22 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_finetuned_nli_jihyun22` is a English model originally trained by Jihyun22. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_nli_jihyun22_en_5.1.4_3.4_1698219140262.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_nli_jihyun22_en_5.1.4_3.4_1698219140262.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_finetuned_nli_jihyun22","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_finetuned_nli_jihyun22","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_finetuned_nli_jihyun22| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.6 MB| + +## References + +https://huggingface.co/Jihyun22/bert-base-finetuned-nli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_finetuned_nli_jiwon_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_finetuned_nli_jiwon_en.md new file mode 100644 index 00000000000000..a61b616216a0de --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_finetuned_nli_jiwon_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_finetuned_nli_jiwon BertForSequenceClassification from JIWON +author: John Snow Labs +name: bert_base_finetuned_nli_jiwon +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_finetuned_nli_jiwon` is a English model originally trained by JIWON. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_nli_jiwon_en_5.1.4_3.4_1698212168796.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_nli_jiwon_en_5.1.4_3.4_1698212168796.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_finetuned_nli_jiwon","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_finetuned_nli_jiwon","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_finetuned_nli_jiwon| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.6 MB| + +## References + +https://huggingface.co/JIWON/bert-base-finetuned-nli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_finetuned_nsmc_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_finetuned_nsmc_en.md new file mode 100644 index 00000000000000..2347d6ac9c7c6a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_finetuned_nsmc_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_finetuned_nsmc BertForSequenceClassification from sunwooooong +author: John Snow Labs +name: bert_base_finetuned_nsmc +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_finetuned_nsmc` is a English model originally trained by sunwooooong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_nsmc_en_5.1.4_3.4_1698193667405.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_nsmc_en_5.1.4_3.4_1698193667405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_finetuned_nsmc","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_finetuned_nsmc","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_finetuned_nsmc| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.6 MB| + +## References + +https://huggingface.co/sunwooooong/bert-base-finetuned-nsmc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_finetuned_ynat_min9805_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_finetuned_ynat_min9805_en.md new file mode 100644 index 00000000000000..1204f5fa94e3e4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_finetuned_ynat_min9805_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_finetuned_ynat_min9805 BertForSequenceClassification from min9805 +author: John Snow Labs +name: bert_base_finetuned_ynat_min9805 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_finetuned_ynat_min9805` is a English model originally trained by min9805. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_ynat_min9805_en_5.1.4_3.4_1698192188964.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_ynat_min9805_en_5.1.4_3.4_1698192188964.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_finetuned_ynat_min9805","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_finetuned_ynat_min9805","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_finetuned_ynat_min9805| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.6 MB| + +## References + +https://huggingface.co/min9805/bert-base-finetuned-ynat \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_finetuned_ynat_yooonsangbeom_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_finetuned_ynat_yooonsangbeom_en.md new file mode 100644 index 00000000000000..3d67f052196ac7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_finetuned_ynat_yooonsangbeom_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_finetuned_ynat_yooonsangbeom BertForSequenceClassification from yooonsangbeom +author: John Snow Labs +name: bert_base_finetuned_ynat_yooonsangbeom +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_finetuned_ynat_yooonsangbeom` is a English model originally trained by yooonsangbeom. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_ynat_yooonsangbeom_en_5.1.4_3.4_1698200316362.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_finetuned_ynat_yooonsangbeom_en_5.1.4_3.4_1698200316362.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_finetuned_ynat_yooonsangbeom","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_finetuned_ynat_yooonsangbeom","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_finetuned_ynat_yooonsangbeom| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.6 MB| + +## References + +https://huggingface.co/yooonsangbeom/bert-base-finetuned-ynat \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_goemotions_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_goemotions_en.md new file mode 100644 index 00000000000000..2e76713c21d194 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_goemotions_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_goemotions BertForSequenceClassification from IsaacZhy +author: John Snow Labs +name: bert_base_goemotions +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_goemotions` is a English model originally trained by IsaacZhy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_goemotions_en_5.1.4_3.4_1698194922222.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_goemotions_en_5.1.4_3.4_1698194922222.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_goemotions","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_goemotions","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_goemotions| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/IsaacZhy/bert-base-goemotions \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_indonesian_522m_finetuned_sentiment_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_indonesian_522m_finetuned_sentiment_en.md new file mode 100644 index 00000000000000..e05636cd292c63 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_indonesian_522m_finetuned_sentiment_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_indonesian_522m_finetuned_sentiment BertForSequenceClassification from poerwiyanto +author: John Snow Labs +name: bert_base_indonesian_522m_finetuned_sentiment +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_indonesian_522m_finetuned_sentiment` is a English model originally trained by poerwiyanto. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_indonesian_522m_finetuned_sentiment_en_5.1.4_3.4_1698209011985.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_indonesian_522m_finetuned_sentiment_en_5.1.4_3.4_1698209011985.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_indonesian_522m_finetuned_sentiment","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_indonesian_522m_finetuned_sentiment","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_indonesian_522m_finetuned_sentiment| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.8 MB| + +## References + +https://huggingface.co/poerwiyanto/bert-base-indonesian-522M-finetuned-sentiment \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_mdoc_bm25_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_mdoc_bm25_en.md new file mode 100644 index 00000000000000..8d013fc00ce1ce --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_mdoc_bm25_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_mdoc_bm25 BertForSequenceClassification from Luyu +author: John Snow Labs +name: bert_base_mdoc_bm25 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_mdoc_bm25` is a English model originally trained by Luyu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_mdoc_bm25_en_5.1.4_3.4_1698221725395.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_mdoc_bm25_en_5.1.4_3.4_1698221725395.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_mdoc_bm25","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_mdoc_bm25","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_mdoc_bm25| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Luyu/bert-base-mdoc-bm25 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_mdoc_hdct_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_mdoc_hdct_en.md new file mode 100644 index 00000000000000..f23947e624bdd2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_mdoc_hdct_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_mdoc_hdct BertForSequenceClassification from Luyu +author: John Snow Labs +name: bert_base_mdoc_hdct +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_mdoc_hdct` is a English model originally trained by Luyu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_mdoc_hdct_en_5.1.4_3.4_1698221922423.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_mdoc_hdct_en_5.1.4_3.4_1698221922423.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_mdoc_hdct","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_mdoc_hdct","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_mdoc_hdct| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Luyu/bert-base-mdoc-hdct \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_multilingual_cased_finetuned_review_xx.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_multilingual_cased_finetuned_review_xx.md new file mode 100644 index 00000000000000..b6973957d233db --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_multilingual_cased_finetuned_review_xx.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_finetuned_review BertForSequenceClassification from seokwoni +author: John Snow Labs +name: bert_base_multilingual_cased_finetuned_review +date: 2023-10-25 +tags: [bert, xx, open_source, sequence_classification, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_finetuned_review` is a Multilingual model originally trained by seokwoni. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_review_xx_5.1.4_3.4_1698217463254.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_finetuned_review_xx_5.1.4_3.4_1698217463254.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_cased_finetuned_review","xx")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_cased_finetuned_review","xx") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_finetuned_review| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/seokwoni/bert-base-multilingual-cased-finetuned-review \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_multilingual_cased_mrpc_glue_xx.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_multilingual_cased_mrpc_glue_xx.md new file mode 100644 index 00000000000000..1a2fecef6fe686 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_multilingual_cased_mrpc_glue_xx.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_cased_mrpc_glue BertForSequenceClassification from rriverar75 +author: John Snow Labs +name: bert_base_multilingual_cased_mrpc_glue +date: 2023-10-25 +tags: [bert, xx, open_source, sequence_classification, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_cased_mrpc_glue` is a Multilingual model originally trained by rriverar75. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_mrpc_glue_xx_5.1.4_3.4_1698230620198.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_cased_mrpc_glue_xx_5.1.4_3.4_1698230620198.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_cased_mrpc_glue","xx")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_cased_mrpc_glue","xx") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_cased_mrpc_glue| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/rriverar75/bert-base-multilingual-cased-mrpc-glue \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_multilingual_uncased_finetuned_news_xx.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_multilingual_uncased_finetuned_news_xx.md new file mode 100644 index 00000000000000..a3343f3a2da4e4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_multilingual_uncased_finetuned_news_xx.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_uncased_finetuned_news BertForSequenceClassification from Tiamz +author: John Snow Labs +name: bert_base_multilingual_uncased_finetuned_news +date: 2023-10-25 +tags: [bert, xx, open_source, sequence_classification, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_uncased_finetuned_news` is a Multilingual model originally trained by Tiamz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_finetuned_news_xx_5.1.4_3.4_1698193892063.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_finetuned_news_xx_5.1.4_3.4_1698193892063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_uncased_finetuned_news","xx")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_uncased_finetuned_news","xx") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_uncased_finetuned_news| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|627.7 MB| + +## References + +https://huggingface.co/Tiamz/bert-base-multilingual-uncased-finetuned-news \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_multilingual_uncased_vietnamese_sentiment_analysis_xx.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_multilingual_uncased_vietnamese_sentiment_analysis_xx.md new file mode 100644 index 00000000000000..79da92f95f576b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_multilingual_uncased_vietnamese_sentiment_analysis_xx.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Multilingual bert_base_multilingual_uncased_vietnamese_sentiment_analysis BertForSequenceClassification from TankuVie +author: John Snow Labs +name: bert_base_multilingual_uncased_vietnamese_sentiment_analysis +date: 2023-10-25 +tags: [bert, xx, open_source, sequence_classification, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_multilingual_uncased_vietnamese_sentiment_analysis` is a Multilingual model originally trained by TankuVie. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_vietnamese_sentiment_analysis_xx_5.1.4_3.4_1698204011669.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_multilingual_uncased_vietnamese_sentiment_analysis_xx_5.1.4_3.4_1698204011669.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_uncased_vietnamese_sentiment_analysis","xx")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_multilingual_uncased_vietnamese_sentiment_analysis","xx") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_multilingual_uncased_vietnamese_sentiment_analysis| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|627.7 MB| + +## References + +https://huggingface.co/TankuVie/bert-base-multilingual-uncased-vietnamese_sentiment_analysis \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_spanish_wwm_cased_finetuned_nlp_ie_4_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_spanish_wwm_cased_finetuned_nlp_ie_4_en.md new file mode 100644 index 00000000000000..0436869be0096f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_spanish_wwm_cased_finetuned_nlp_ie_4_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_spanish_wwm_cased_finetuned_nlp_ie_4 BertForSequenceClassification from Willy +author: John Snow Labs +name: bert_base_spanish_wwm_cased_finetuned_nlp_ie_4 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_spanish_wwm_cased_finetuned_nlp_ie_4` is a English model originally trained by Willy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_finetuned_nlp_ie_4_en_5.1.4_3.4_1698192192250.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_cased_finetuned_nlp_ie_4_en_5.1.4_3.4_1698192192250.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_spanish_wwm_cased_finetuned_nlp_ie_4","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_spanish_wwm_cased_finetuned_nlp_ie_4","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_spanish_wwm_cased_finetuned_nlp_ie_4| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.7 MB| + +## References + +https://huggingface.co/Willy/bert-base-spanish-wwm-cased-finetuned-NLP-IE-4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_spanish_wwm_uncased_finetuned_pawsx_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_spanish_wwm_uncased_finetuned_pawsx_en.md new file mode 100644 index 00000000000000..00a2d33da091db --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_spanish_wwm_uncased_finetuned_pawsx_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_spanish_wwm_uncased_finetuned_pawsx BertForSequenceClassification from dccuchile +author: John Snow Labs +name: bert_base_spanish_wwm_uncased_finetuned_pawsx +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_spanish_wwm_uncased_finetuned_pawsx` is a English model originally trained by dccuchile. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_uncased_finetuned_pawsx_en_5.1.4_3.4_1698192063016.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_uncased_finetuned_pawsx_en_5.1.4_3.4_1698192063016.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_spanish_wwm_uncased_finetuned_pawsx","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_spanish_wwm_uncased_finetuned_pawsx","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_spanish_wwm_uncased_finetuned_pawsx| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.9 MB| + +## References + +https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased-finetuned-pawsx \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_spanish_wwm_uncased_finetuned_xnli_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_spanish_wwm_uncased_finetuned_xnli_en.md new file mode 100644 index 00000000000000..f1aa1b66edca3b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_spanish_wwm_uncased_finetuned_xnli_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_spanish_wwm_uncased_finetuned_xnli BertForSequenceClassification from dccuchile +author: John Snow Labs +name: bert_base_spanish_wwm_uncased_finetuned_xnli +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_spanish_wwm_uncased_finetuned_xnli` is a English model originally trained by dccuchile. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_uncased_finetuned_xnli_en_5.1.4_3.4_1698192235864.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_spanish_wwm_uncased_finetuned_xnli_en_5.1.4_3.4_1698192235864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_spanish_wwm_uncased_finetuned_xnli","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_spanish_wwm_uncased_finetuned_xnli","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_spanish_wwm_uncased_finetuned_xnli| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.9 MB| + +## References + +https://huggingface.co/dccuchile/bert-base-spanish-wwm-uncased-finetuned-xnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncase_contracts_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncase_contracts_en.md new file mode 100644 index 00000000000000..06a32d6678f25b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncase_contracts_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncase_contracts BertForSequenceClassification from amanbawa96 +author: John Snow Labs +name: bert_base_uncase_contracts +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncase_contracts` is a English model originally trained by amanbawa96. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncase_contracts_en_5.1.4_3.4_1698263890692.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncase_contracts_en_5.1.4_3.4_1698263890692.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncase_contracts","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncase_contracts","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncase_contracts| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/amanbawa96/bert-base-uncase-contracts \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_ade_ade_corpus_v2_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_ade_ade_corpus_v2_en.md new file mode 100644 index 00000000000000..78fae46dc05da7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_ade_ade_corpus_v2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_ade_ade_corpus_v2 BertForSequenceClassification from Jorgeutd +author: John Snow Labs +name: bert_base_uncased_ade_ade_corpus_v2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ade_ade_corpus_v2` is a English model originally trained by Jorgeutd. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ade_ade_corpus_v2_en_5.1.4_3.4_1698219322282.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ade_ade_corpus_v2_en_5.1.4_3.4_1698219322282.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_ade_ade_corpus_v2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_ade_ade_corpus_v2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_ade_ade_corpus_v2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jorgeutd/bert-base-uncased-ade-Ade-corpus-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_ag_news_finetuned_dwnews_categories_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_ag_news_finetuned_dwnews_categories_en.md new file mode 100644 index 00000000000000..fdfa063057616a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_ag_news_finetuned_dwnews_categories_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_ag_news_finetuned_dwnews_categories BertForSequenceClassification from tillschwoerer +author: John Snow Labs +name: bert_base_uncased_ag_news_finetuned_dwnews_categories +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ag_news_finetuned_dwnews_categories` is a English model originally trained by tillschwoerer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ag_news_finetuned_dwnews_categories_en_5.1.4_3.4_1698217799442.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ag_news_finetuned_dwnews_categories_en_5.1.4_3.4_1698217799442.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_ag_news_finetuned_dwnews_categories","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_ag_news_finetuned_dwnews_categories","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_ag_news_finetuned_dwnews_categories| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/tillschwoerer/bert-base-uncased-ag-news-finetuned-dwnews-categories \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_cola_2e_5_21_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_cola_2e_5_21_en.md new file mode 100644 index 00000000000000..edd7d6a8b48232 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_cola_2e_5_21_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_avg_cola_2e_5_21 BertForSequenceClassification from TehranNLP-org +author: John Snow Labs +name: bert_base_uncased_avg_cola_2e_5_21 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_avg_cola_2e_5_21` is a English model originally trained by TehranNLP-org. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_avg_cola_2e_5_21_en_5.1.4_3.4_1698256190441.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_avg_cola_2e_5_21_en_5.1.4_3.4_1698256190441.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_avg_cola_2e_5_21","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_avg_cola_2e_5_21","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_avg_cola_2e_5_21| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/TehranNLP-org/bert-base-uncased-avg-cola-2e-5-21 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_cola_2e_5_42_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_cola_2e_5_42_en.md new file mode 100644 index 00000000000000..82a0600fa2e057 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_cola_2e_5_42_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_avg_cola_2e_5_42 BertForSequenceClassification from TehranNLP-org +author: John Snow Labs +name: bert_base_uncased_avg_cola_2e_5_42 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_avg_cola_2e_5_42` is a English model originally trained by TehranNLP-org. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_avg_cola_2e_5_42_en_5.1.4_3.4_1698257229443.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_avg_cola_2e_5_42_en_5.1.4_3.4_1698257229443.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_avg_cola_2e_5_42","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_avg_cola_2e_5_42","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_avg_cola_2e_5_42| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/TehranNLP-org/bert-base-uncased-avg-cola-2e-5-42 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_cola_2e_5_63_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_cola_2e_5_63_en.md new file mode 100644 index 00000000000000..9e99ff5bd17be5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_cola_2e_5_63_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_avg_cola_2e_5_63 BertForSequenceClassification from TehranNLP-org +author: John Snow Labs +name: bert_base_uncased_avg_cola_2e_5_63 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_avg_cola_2e_5_63` is a English model originally trained by TehranNLP-org. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_avg_cola_2e_5_63_en_5.1.4_3.4_1698258140167.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_avg_cola_2e_5_63_en_5.1.4_3.4_1698258140167.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_avg_cola_2e_5_63","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_avg_cola_2e_5_63","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_avg_cola_2e_5_63| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/TehranNLP-org/bert-base-uncased-avg-cola-2e-5-63 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_mnli_2e_5_21_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_mnli_2e_5_21_en.md new file mode 100644 index 00000000000000..3865df2545f283 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_mnli_2e_5_21_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_avg_mnli_2e_5_21 BertForSequenceClassification from TehranNLP-org +author: John Snow Labs +name: bert_base_uncased_avg_mnli_2e_5_21 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_avg_mnli_2e_5_21` is a English model originally trained by TehranNLP-org. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_avg_mnli_2e_5_21_en_5.1.4_3.4_1698259076415.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_avg_mnli_2e_5_21_en_5.1.4_3.4_1698259076415.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_avg_mnli_2e_5_21","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_avg_mnli_2e_5_21","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_avg_mnli_2e_5_21| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/TehranNLP-org/bert-base-uncased-avg-mnli-2e-5-21 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_mnli_2e_5_63_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_mnli_2e_5_63_en.md new file mode 100644 index 00000000000000..f46d48b303686b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_mnli_2e_5_63_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_avg_mnli_2e_5_63 BertForSequenceClassification from TehranNLP-org +author: John Snow Labs +name: bert_base_uncased_avg_mnli_2e_5_63 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_avg_mnli_2e_5_63` is a English model originally trained by TehranNLP-org. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_avg_mnli_2e_5_63_en_5.1.4_3.4_1698259748434.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_avg_mnli_2e_5_63_en_5.1.4_3.4_1698259748434.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_avg_mnli_2e_5_63","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_avg_mnli_2e_5_63","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_avg_mnli_2e_5_63| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/TehranNLP-org/bert-base-uncased-avg-mnli-2e-5-63 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_mnli_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_mnli_en.md new file mode 100644 index 00000000000000..5c021fab151414 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_mnli_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_avg_mnli BertForSequenceClassification from TehranNLP-org +author: John Snow Labs +name: bert_base_uncased_avg_mnli +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_avg_mnli` is a English model originally trained by TehranNLP-org. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_avg_mnli_en_5.1.4_3.4_1698260656942.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_avg_mnli_en_5.1.4_3.4_1698260656942.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_avg_mnli","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_avg_mnli","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_avg_mnli| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/TehranNLP-org/bert-base-uncased-avg-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_sst2_2e_5_21_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_sst2_2e_5_21_en.md new file mode 100644 index 00000000000000..63856260d44f74 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_sst2_2e_5_21_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_avg_sst2_2e_5_21 BertForSequenceClassification from TehranNLP-org +author: John Snow Labs +name: bert_base_uncased_avg_sst2_2e_5_21 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_avg_sst2_2e_5_21` is a English model originally trained by TehranNLP-org. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_avg_sst2_2e_5_21_en_5.1.4_3.4_1698261608243.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_avg_sst2_2e_5_21_en_5.1.4_3.4_1698261608243.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_avg_sst2_2e_5_21","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_avg_sst2_2e_5_21","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_avg_sst2_2e_5_21| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/TehranNLP-org/bert-base-uncased-avg-sst2-2e-5-21 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_sst2_2e_5_42_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_sst2_2e_5_42_en.md new file mode 100644 index 00000000000000..0c48df8116e3b3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_sst2_2e_5_42_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_avg_sst2_2e_5_42 BertForSequenceClassification from TehranNLP-org +author: John Snow Labs +name: bert_base_uncased_avg_sst2_2e_5_42 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_avg_sst2_2e_5_42` is a English model originally trained by TehranNLP-org. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_avg_sst2_2e_5_42_en_5.1.4_3.4_1698262417809.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_avg_sst2_2e_5_42_en_5.1.4_3.4_1698262417809.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_avg_sst2_2e_5_42","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_avg_sst2_2e_5_42","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_avg_sst2_2e_5_42| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/TehranNLP-org/bert-base-uncased-avg-sst2-2e-5-42 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_sst2_2e_5_63_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_sst2_2e_5_63_en.md new file mode 100644 index 00000000000000..572000aa72b2ad --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_avg_sst2_2e_5_63_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_avg_sst2_2e_5_63 BertForSequenceClassification from TehranNLP-org +author: John Snow Labs +name: bert_base_uncased_avg_sst2_2e_5_63 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_avg_sst2_2e_5_63` is a English model originally trained by TehranNLP-org. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_avg_sst2_2e_5_63_en_5.1.4_3.4_1698263251300.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_avg_sst2_2e_5_63_en_5.1.4_3.4_1698263251300.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_avg_sst2_2e_5_63","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_avg_sst2_2e_5_63","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_avg_sst2_2e_5_63| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/TehranNLP-org/bert-base-uncased-avg-sst2-2e-5-63 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_cls_hatexplain_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_cls_hatexplain_en.md new file mode 100644 index 00000000000000..c540ccd75a84f9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_cls_hatexplain_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_cls_hatexplain BertForSequenceClassification from TehranNLP-org +author: John Snow Labs +name: bert_base_uncased_cls_hatexplain +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_cls_hatexplain` is a English model originally trained by TehranNLP-org. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_cls_hatexplain_en_5.1.4_3.4_1698264097575.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_cls_hatexplain_en_5.1.4_3.4_1698264097575.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_cls_hatexplain","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_cls_hatexplain","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_cls_hatexplain| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/TehranNLP-org/bert-base-uncased-cls-hatexplain \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_cls_mnli_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_cls_mnli_en.md new file mode 100644 index 00000000000000..c475b751051246 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_cls_mnli_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_cls_mnli BertForSequenceClassification from TehranNLP-org +author: John Snow Labs +name: bert_base_uncased_cls_mnli +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_cls_mnli` is a English model originally trained by TehranNLP-org. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_cls_mnli_en_5.1.4_3.4_1698264715258.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_cls_mnli_en_5.1.4_3.4_1698264715258.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_cls_mnli","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_cls_mnli","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_cls_mnli| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/TehranNLP-org/bert-base-uncased-cls-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_cls_sst2_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_cls_sst2_en.md new file mode 100644 index 00000000000000..b794fc15525399 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_cls_sst2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_cls_sst2 BertForSequenceClassification from TehranNLP-org +author: John Snow Labs +name: bert_base_uncased_cls_sst2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_cls_sst2` is a English model originally trained by TehranNLP-org. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_cls_sst2_en_5.1.4_3.4_1698265490203.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_cls_sst2_en_5.1.4_3.4_1698265490203.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_cls_sst2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_cls_sst2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_cls_sst2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/TehranNLP-org/bert-base-uncased-cls-sst2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_cola_jeremiahz_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_cola_jeremiahz_en.md new file mode 100644 index 00000000000000..5b128e9f296c15 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_cola_jeremiahz_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_cola_jeremiahz BertForSequenceClassification from JeremiahZ +author: John Snow Labs +name: bert_base_uncased_cola_jeremiahz +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_cola_jeremiahz` is a English model originally trained by JeremiahZ. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_cola_jeremiahz_en_5.1.4_3.4_1698193095882.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_cola_jeremiahz_en_5.1.4_3.4_1698193095882.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_cola_jeremiahz","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_cola_jeremiahz","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_cola_jeremiahz| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/JeremiahZ/bert-base-uncased-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_emotion_damamsaketh19_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_emotion_damamsaketh19_en.md new file mode 100644 index 00000000000000..234225fc44a696 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_emotion_damamsaketh19_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_emotion_damamsaketh19 BertForSequenceClassification from damamsaketh19 +author: John Snow Labs +name: bert_base_uncased_emotion_damamsaketh19 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_emotion_damamsaketh19` is a English model originally trained by damamsaketh19. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotion_damamsaketh19_en_5.1.4_3.4_1698268726136.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_emotion_damamsaketh19_en_5.1.4_3.4_1698268726136.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_emotion_damamsaketh19","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_emotion_damamsaketh19","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_emotion_damamsaketh19| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/damamsaketh19/bert-base-uncased-emotion \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finance_sentiment_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finance_sentiment_en.md new file mode 100644 index 00000000000000..c8d758f12233f9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finance_sentiment_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finance_sentiment BertForSequenceClassification from nickwong64 +author: John Snow Labs +name: bert_base_uncased_finance_sentiment +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finance_sentiment` is a English model originally trained by nickwong64. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finance_sentiment_en_5.1.4_3.4_1698199792868.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finance_sentiment_en_5.1.4_3.4_1698199792868.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finance_sentiment","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finance_sentiment","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finance_sentiment| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/nickwong64/bert-base-uncased-finance-sentiment \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_fine_tuned_on_clinc_oos_dataset_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_fine_tuned_on_clinc_oos_dataset_en.md new file mode 100644 index 00000000000000..abc4019940e9ef --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_fine_tuned_on_clinc_oos_dataset_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_fine_tuned_on_clinc_oos_dataset BertForSequenceClassification from itzo +author: John Snow Labs +name: bert_base_uncased_fine_tuned_on_clinc_oos_dataset +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_fine_tuned_on_clinc_oos_dataset` is a English model originally trained by itzo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_fine_tuned_on_clinc_oos_dataset_en_5.1.4_3.4_1698212599389.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_fine_tuned_on_clinc_oos_dataset_en_5.1.4_3.4_1698212599389.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_fine_tuned_on_clinc_oos_dataset","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_fine_tuned_on_clinc_oos_dataset","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_fine_tuned_on_clinc_oos_dataset| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.8 MB| + +## References + +https://huggingface.co/itzo/bert-base-uncased-fine-tuned-on-clinc_oos-dataset \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned1_claqua_cqa_entity_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned1_claqua_cqa_entity_en.md new file mode 100644 index 00000000000000..53478598f8871b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned1_claqua_cqa_entity_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned1_claqua_cqa_entity BertForSequenceClassification from sasuke +author: John Snow Labs +name: bert_base_uncased_finetuned1_claqua_cqa_entity +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned1_claqua_cqa_entity` is a English model originally trained by sasuke. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned1_claqua_cqa_entity_en_5.1.4_3.4_1698212967435.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned1_claqua_cqa_entity_en_5.1.4_3.4_1698212967435.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned1_claqua_cqa_entity","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned1_claqua_cqa_entity","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned1_claqua_cqa_entity| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/sasuke/bert-base-uncased-finetuned1-claqua_cqa_entity \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_0505_2_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_0505_2_en.md new file mode 100644 index 00000000000000..d464a33428cbe2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_0505_2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_0505_2 BertForSequenceClassification from YeRyeongLee +author: John Snow Labs +name: bert_base_uncased_finetuned_0505_2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_0505_2` is a English model originally trained by YeRyeongLee. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_0505_2_en_5.1.4_3.4_1698201594219.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_0505_2_en_5.1.4_3.4_1698201594219.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_0505_2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_0505_2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_0505_2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/YeRyeongLee/bert-base-uncased-finetuned-0505-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_binary_classification_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_binary_classification_en.md new file mode 100644 index 00000000000000..1b3b285f15d434 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_binary_classification_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_binary_classification BertForSequenceClassification from nielsr +author: John Snow Labs +name: bert_base_uncased_finetuned_binary_classification +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_binary_classification` is a English model originally trained by nielsr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_binary_classification_en_5.1.4_3.4_1698259651090.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_binary_classification_en_5.1.4_3.4_1698259651090.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_binary_classification","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_binary_classification","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_binary_classification| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/nielsr/bert-base-uncased-finetuned-binary-classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_claqua_cqa_predicate_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_claqua_cqa_predicate_en.md new file mode 100644 index 00000000000000..f88888d93dd572 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_claqua_cqa_predicate_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_claqua_cqa_predicate BertForSequenceClassification from sasuke +author: John Snow Labs +name: bert_base_uncased_finetuned_claqua_cqa_predicate +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_claqua_cqa_predicate` is a English model originally trained by sasuke. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_claqua_cqa_predicate_en_5.1.4_3.4_1698212787474.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_claqua_cqa_predicate_en_5.1.4_3.4_1698212787474.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_claqua_cqa_predicate","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_claqua_cqa_predicate","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_claqua_cqa_predicate| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/sasuke/bert-base-uncased-finetuned-claqua_cqa_predicate \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_claqua_cqi_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_claqua_cqi_en.md new file mode 100644 index 00000000000000..f7a32d4bfc8a66 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_claqua_cqi_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_claqua_cqi BertForSequenceClassification from sasuke +author: John Snow Labs +name: bert_base_uncased_finetuned_claqua_cqi +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_claqua_cqi` is a English model originally trained by sasuke. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_claqua_cqi_en_5.1.4_3.4_1698212427493.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_claqua_cqi_en_5.1.4_3.4_1698212427493.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_claqua_cqi","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_claqua_cqi","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_claqua_cqi| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/sasuke/bert-base-uncased-finetuned-claqua_cqi \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_cola_ajrae_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_cola_ajrae_en.md new file mode 100644 index 00000000000000..f2cbbab4d23c01 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_cola_ajrae_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_ajrae BertForSequenceClassification from ajrae +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_ajrae +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_ajrae` is a English model originally trained by ajrae. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_ajrae_en_5.1.4_3.4_1698278372008.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_ajrae_en_5.1.4_3.4_1698278372008.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_ajrae","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_ajrae","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_ajrae| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ajrae/bert-base-uncased-finetuned-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_cola_ruizhou_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_cola_ruizhou_en.md new file mode 100644 index 00000000000000..f4c5c411b5d34a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_cola_ruizhou_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_ruizhou BertForSequenceClassification from Ruizhou +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_ruizhou +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_ruizhou` is a English model originally trained by Ruizhou. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_ruizhou_en_5.1.4_3.4_1698245116739.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_ruizhou_en_5.1.4_3.4_1698245116739.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_ruizhou","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_ruizhou","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_ruizhou| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Ruizhou/bert-base-uncased-finetuned-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_cola_zhsj16_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_cola_zhsj16_en.md new file mode 100644 index 00000000000000..64da5a96fb748d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_cola_zhsj16_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_zhsj16 BertForSequenceClassification from zhsj16 +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_zhsj16 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_zhsj16` is a English model originally trained by zhsj16. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_zhsj16_en_5.1.4_3.4_1698198384959.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_zhsj16_en_5.1.4_3.4_1698198384959.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_zhsj16","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_zhsj16","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_zhsj16| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/zhsj16/bert-base-uncased-finetuned-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_effectiveness_dagstuhl_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_effectiveness_dagstuhl_en.md new file mode 100644 index 00000000000000..546e80797ba437 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_effectiveness_dagstuhl_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_effectiveness_dagstuhl BertForSequenceClassification from jakub014 +author: John Snow Labs +name: bert_base_uncased_finetuned_effectiveness_dagstuhl +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_effectiveness_dagstuhl` is a English model originally trained by jakub014. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_effectiveness_dagstuhl_en_5.1.4_3.4_1698199183322.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_effectiveness_dagstuhl_en_5.1.4_3.4_1698199183322.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_effectiveness_dagstuhl","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_effectiveness_dagstuhl","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_effectiveness_dagstuhl| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jakub014/bert-base-uncased-finetuned-effectiveness-dagstuhl \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_effectiveness_redditcmv_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_effectiveness_redditcmv_en.md new file mode 100644 index 00000000000000..959b8485fb9c5e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_effectiveness_redditcmv_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_effectiveness_redditcmv BertForSequenceClassification from jakub014 +author: John Snow Labs +name: bert_base_uncased_finetuned_effectiveness_redditcmv +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_effectiveness_redditcmv` is a English model originally trained by jakub014. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_effectiveness_redditcmv_en_5.1.4_3.4_1698193029636.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_effectiveness_redditcmv_en_5.1.4_3.4_1698193029636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_effectiveness_redditcmv","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_effectiveness_redditcmv","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_effectiveness_redditcmv| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jakub014/bert-base-uncased-finetuned-effectiveness-redditCMV \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_for_sentiment_analysis1_sst2_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_for_sentiment_analysis1_sst2_en.md new file mode 100644 index 00000000000000..6d2a4ee5ca9200 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_for_sentiment_analysis1_sst2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_for_sentiment_analysis1_sst2 BertForSequenceClassification from Ghost1 +author: John Snow Labs +name: bert_base_uncased_finetuned_for_sentiment_analysis1_sst2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_for_sentiment_analysis1_sst2` is a English model originally trained by Ghost1. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_for_sentiment_analysis1_sst2_en_5.1.4_3.4_1698202182930.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_for_sentiment_analysis1_sst2_en_5.1.4_3.4_1698202182930.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_for_sentiment_analysis1_sst2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_for_sentiment_analysis1_sst2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_for_sentiment_analysis1_sst2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Ghost1/bert-base-uncased-finetuned_for_sentiment_analysis1-sst2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_glue_mrpc_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_glue_mrpc_en.md new file mode 100644 index 00000000000000..862691cf2ec086 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_glue_mrpc_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_glue_mrpc BertForSequenceClassification from lrs21 +author: John Snow Labs +name: bert_base_uncased_finetuned_glue_mrpc +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_glue_mrpc` is a English model originally trained by lrs21. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_glue_mrpc_en_5.1.4_3.4_1698207965889.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_glue_mrpc_en_5.1.4_3.4_1698207965889.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_glue_mrpc","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_glue_mrpc","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_glue_mrpc| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/lrs21/bert-base-uncased-finetuned-glue-mrpc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_hateful_meme_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_hateful_meme_en.md new file mode 100644 index 00000000000000..981f61563c0a60 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_hateful_meme_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_hateful_meme BertForSequenceClassification from tommilyjones +author: John Snow Labs +name: bert_base_uncased_finetuned_hateful_meme +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_hateful_meme` is a English model originally trained by tommilyjones. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_hateful_meme_en_5.1.4_3.4_1698218460479.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_hateful_meme_en_5.1.4_3.4_1698218460479.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_hateful_meme","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_hateful_meme","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_hateful_meme| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/tommilyjones/bert-base-uncased-finetuned-hateful-meme \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap2_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap2_en.md new file mode 100644 index 00000000000000..e36ecf8fb073f3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_iemocap2 BertForSequenceClassification from Zahra99 +author: John Snow Labs +name: bert_base_uncased_finetuned_iemocap2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_iemocap2` is a English model originally trained by Zahra99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_iemocap2_en_5.1.4_3.4_1698214367259.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_iemocap2_en_5.1.4_3.4_1698214367259.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_iemocap2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_iemocap2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_iemocap2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Zahra99/bert-base-uncased-finetuned-iemocap2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap4_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap4_en.md new file mode 100644 index 00000000000000..cd56cc076f64b3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap4_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_iemocap4 BertForSequenceClassification from Zahra99 +author: John Snow Labs +name: bert_base_uncased_finetuned_iemocap4 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_iemocap4` is a English model originally trained by Zahra99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_iemocap4_en_5.1.4_3.4_1698215069499.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_iemocap4_en_5.1.4_3.4_1698215069499.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_iemocap4","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_iemocap4","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_iemocap4| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Zahra99/bert-base-uncased-finetuned-iemocap4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap5_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap5_en.md new file mode 100644 index 00000000000000..921f74d5626680 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap5_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_iemocap5 BertForSequenceClassification from Zahra99 +author: John Snow Labs +name: bert_base_uncased_finetuned_iemocap5 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_iemocap5` is a English model originally trained by Zahra99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_iemocap5_en_5.1.4_3.4_1698215514278.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_iemocap5_en_5.1.4_3.4_1698215514278.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_iemocap5","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_iemocap5","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_iemocap5| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Zahra99/bert-base-uncased-finetuned-iemocap5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap7_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap7_en.md new file mode 100644 index 00000000000000..603ab0ef86eec5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap7_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_iemocap7 BertForSequenceClassification from Zahra99 +author: John Snow Labs +name: bert_base_uncased_finetuned_iemocap7 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_iemocap7` is a English model originally trained by Zahra99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_iemocap7_en_5.1.4_3.4_1698216905227.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_iemocap7_en_5.1.4_3.4_1698216905227.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_iemocap7","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_iemocap7","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_iemocap7| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Zahra99/bert-base-uncased-finetuned-iemocap7 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap8_en.md new file mode 100644 index 00000000000000..73da2090940030 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_iemocap8 BertForSequenceClassification from Zahra99 +author: John Snow Labs +name: bert_base_uncased_finetuned_iemocap8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_iemocap8` is a English model originally trained by Zahra99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_iemocap8_en_5.1.4_3.4_1698217066933.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_iemocap8_en_5.1.4_3.4_1698217066933.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_iemocap8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_iemocap8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_iemocap8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Zahra99/bert-base-uncased-finetuned-iemocap8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap_en.md new file mode 100644 index 00000000000000..5c60d3607874ef --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_iemocap BertForSequenceClassification from Zahra99 +author: John Snow Labs +name: bert_base_uncased_finetuned_iemocap +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_iemocap` is a English model originally trained by Zahra99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_iemocap_en_5.1.4_3.4_1698213282225.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_iemocap_en_5.1.4_3.4_1698213282225.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_iemocap","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_iemocap","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_iemocap| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Zahra99/bert-base-uncased-finetuned-iemocap \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap_uptuna2_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap_uptuna2_en.md new file mode 100644 index 00000000000000..c3f77f2231298a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap_uptuna2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_iemocap_uptuna2 BertForSequenceClassification from Zahra99 +author: John Snow Labs +name: bert_base_uncased_finetuned_iemocap_uptuna2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_iemocap_uptuna2` is a English model originally trained by Zahra99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_iemocap_uptuna2_en_5.1.4_3.4_1698213797050.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_iemocap_uptuna2_en_5.1.4_3.4_1698213797050.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_iemocap_uptuna2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_iemocap_uptuna2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_iemocap_uptuna2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Zahra99/bert-base-uncased-finetuned-iemocap-uptuna2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap_uptuna3_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap_uptuna3_en.md new file mode 100644 index 00000000000000..eed57f261737a2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap_uptuna3_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_iemocap_uptuna3 BertForSequenceClassification from Zahra99 +author: John Snow Labs +name: bert_base_uncased_finetuned_iemocap_uptuna3 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_iemocap_uptuna3` is a English model originally trained by Zahra99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_iemocap_uptuna3_en_5.1.4_3.4_1698214553247.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_iemocap_uptuna3_en_5.1.4_3.4_1698214553247.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_iemocap_uptuna3","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_iemocap_uptuna3","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_iemocap_uptuna3| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Zahra99/bert-base-uncased-finetuned-iemocap-uptuna3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap_uptuna5_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap_uptuna5_en.md new file mode 100644 index 00000000000000..db9bce6905c22f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap_uptuna5_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_iemocap_uptuna5 BertForSequenceClassification from Zahra99 +author: John Snow Labs +name: bert_base_uncased_finetuned_iemocap_uptuna5 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_iemocap_uptuna5` is a English model originally trained by Zahra99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_iemocap_uptuna5_en_5.1.4_3.4_1698216567381.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_iemocap_uptuna5_en_5.1.4_3.4_1698216567381.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_iemocap_uptuna5","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_iemocap_uptuna5","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_iemocap_uptuna5| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Zahra99/bert-base-uncased-finetuned-iemocap-uptuna5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap_uptuna6_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap_uptuna6_en.md new file mode 100644 index 00000000000000..a20ff579a30fd6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap_uptuna6_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_iemocap_uptuna6 BertForSequenceClassification from Zahra99 +author: John Snow Labs +name: bert_base_uncased_finetuned_iemocap_uptuna6 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_iemocap_uptuna6` is a English model originally trained by Zahra99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_iemocap_uptuna6_en_5.1.4_3.4_1698216741320.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_iemocap_uptuna6_en_5.1.4_3.4_1698216741320.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_iemocap_uptuna6","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_iemocap_uptuna6","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_iemocap_uptuna6| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Zahra99/bert-base-uncased-finetuned-iemocap-uptuna6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap_uptuna_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap_uptuna_en.md new file mode 100644 index 00000000000000..c5afe144015597 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_iemocap_uptuna_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_iemocap_uptuna BertForSequenceClassification from Zahra99 +author: John Snow Labs +name: bert_base_uncased_finetuned_iemocap_uptuna +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_iemocap_uptuna` is a English model originally trained by Zahra99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_iemocap_uptuna_en_5.1.4_3.4_1698213632291.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_iemocap_uptuna_en_5.1.4_3.4_1698213632291.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_iemocap_uptuna","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_iemocap_uptuna","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_iemocap_uptuna| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Zahra99/bert-base-uncased-finetuned-iemocap-uptuna \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_kaggle_predicting_effective_arguments_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_kaggle_predicting_effective_arguments_en.md new file mode 100644 index 00000000000000..dccac789f6e3f6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_kaggle_predicting_effective_arguments_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_kaggle_predicting_effective_arguments BertForSequenceClassification from mgfrantz +author: John Snow Labs +name: bert_base_uncased_finetuned_kaggle_predicting_effective_arguments +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_kaggle_predicting_effective_arguments` is a English model originally trained by mgfrantz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_kaggle_predicting_effective_arguments_en_5.1.4_3.4_1698210269374.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_kaggle_predicting_effective_arguments_en_5.1.4_3.4_1698210269374.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_kaggle_predicting_effective_arguments","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_kaggle_predicting_effective_arguments","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_kaggle_predicting_effective_arguments| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/mgfrantz/bert_base_uncased_finetuned_kaggle_predicting_effective_arguments \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_mrpc_hilariooliveira_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_mrpc_hilariooliveira_en.md new file mode 100644 index 00000000000000..7a312b503d735c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_mrpc_hilariooliveira_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_mrpc_hilariooliveira BertForSequenceClassification from hilariooliveira +author: John Snow Labs +name: bert_base_uncased_finetuned_mrpc_hilariooliveira +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_mrpc_hilariooliveira` is a English model originally trained by hilariooliveira. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mrpc_hilariooliveira_en_5.1.4_3.4_1698219891498.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mrpc_hilariooliveira_en_5.1.4_3.4_1698219891498.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_mrpc_hilariooliveira","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_mrpc_hilariooliveira","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_mrpc_hilariooliveira| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/hilariooliveira/bert-base-uncased-finetuned-mrpc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_mrpc_ruizhou_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_mrpc_ruizhou_en.md new file mode 100644 index 00000000000000..3ffc3b947b8ed0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_mrpc_ruizhou_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_mrpc_ruizhou BertForSequenceClassification from Ruizhou +author: John Snow Labs +name: bert_base_uncased_finetuned_mrpc_ruizhou +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_mrpc_ruizhou` is a English model originally trained by Ruizhou. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mrpc_ruizhou_en_5.1.4_3.4_1698245908228.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mrpc_ruizhou_en_5.1.4_3.4_1698245908228.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_mrpc_ruizhou","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_mrpc_ruizhou","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_mrpc_ruizhou| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Ruizhou/bert-base-uncased-finetuned-mrpc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_multiglue_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_multiglue_en.md new file mode 100644 index 00000000000000..b581ead266ed54 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_multiglue_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_multiglue BertForSequenceClassification from MtCelesteMa +author: John Snow Labs +name: bert_base_uncased_finetuned_multiglue +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_multiglue` is a English model originally trained by MtCelesteMa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_multiglue_en_5.1.4_3.4_1698192369362.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_multiglue_en_5.1.4_3.4_1698192369362.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_multiglue","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_multiglue","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_multiglue| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/MtCelesteMa/bert-base-uncased-finetuned-multiglue \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_osdg_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_osdg_en.md new file mode 100644 index 00000000000000..169987921a7ef2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_osdg_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_osdg BertForSequenceClassification from ppsingh +author: John Snow Labs +name: bert_base_uncased_finetuned_osdg +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_osdg` is a English model originally trained by ppsingh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_osdg_en_5.1.4_3.4_1698278330539.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_osdg_en_5.1.4_3.4_1698278330539.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_osdg","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_osdg","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_osdg| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ppsingh/bert-base-uncased-finetuned-osdg \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_question_v_statement_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_question_v_statement_en.md new file mode 100644 index 00000000000000..a64c63361d443f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_question_v_statement_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_question_v_statement BertForSequenceClassification from mafwalter +author: John Snow Labs +name: bert_base_uncased_finetuned_question_v_statement +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_question_v_statement` is a English model originally trained by mafwalter. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_question_v_statement_en_5.1.4_3.4_1698222726543.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_question_v_statement_en_5.1.4_3.4_1698222726543.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_question_v_statement","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_question_v_statement","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_question_v_statement| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/mafwalter/bert-base-uncased-finetuned-question-v-statement \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_rte_joqsan_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_rte_joqsan_en.md new file mode 100644 index 00000000000000..6ed96a24e475e9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_rte_joqsan_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_rte_joqsan BertForSequenceClassification from Joqsan +author: John Snow Labs +name: bert_base_uncased_finetuned_rte_joqsan +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_rte_joqsan` is a English model originally trained by Joqsan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_rte_joqsan_en_5.1.4_3.4_1698192184739.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_rte_joqsan_en_5.1.4_3.4_1698192184739.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_rte_joqsan","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_rte_joqsan","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_rte_joqsan| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Joqsan/bert-base-uncased-finetuned-rte \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_rte_ruizhou_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_rte_ruizhou_en.md new file mode 100644 index 00000000000000..83da10bd745d40 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_rte_ruizhou_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_rte_ruizhou BertForSequenceClassification from Ruizhou +author: John Snow Labs +name: bert_base_uncased_finetuned_rte_ruizhou +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_rte_ruizhou` is a English model originally trained by Ruizhou. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_rte_ruizhou_en_5.1.4_3.4_1698246671592.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_rte_ruizhou_en_5.1.4_3.4_1698246671592.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_rte_ruizhou","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_rte_ruizhou","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_rte_ruizhou| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Ruizhou/bert-base-uncased-finetuned-rte \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_small_0505_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_small_0505_en.md new file mode 100644 index 00000000000000..7ce679a0cf8eb7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_small_0505_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_small_0505 BertForSequenceClassification from YeRyeongLee +author: John Snow Labs +name: bert_base_uncased_finetuned_small_0505 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_small_0505` is a English model originally trained by YeRyeongLee. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_small_0505_en_5.1.4_3.4_1698201242766.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_small_0505_en_5.1.4_3.4_1698201242766.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_small_0505","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_small_0505","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_small_0505| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/YeRyeongLee/bert-base-uncased-finetuned-small-0505 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_sufficiency_dagstuhl_otherseeds_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_sufficiency_dagstuhl_otherseeds_en.md new file mode 100644 index 00000000000000..a82619a1ceb14c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_sufficiency_dagstuhl_otherseeds_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_sufficiency_dagstuhl_otherseeds BertForSequenceClassification from jakub014 +author: John Snow Labs +name: bert_base_uncased_finetuned_sufficiency_dagstuhl_otherseeds +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_sufficiency_dagstuhl_otherseeds` is a English model originally trained by jakub014. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_sufficiency_dagstuhl_otherseeds_en_5.1.4_3.4_1698212451801.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_sufficiency_dagstuhl_otherseeds_en_5.1.4_3.4_1698212451801.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_sufficiency_dagstuhl_otherseeds","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_sufficiency_dagstuhl_otherseeds","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_sufficiency_dagstuhl_otherseeds| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jakub014/bert-base-uncased-finetuned-sufficiency-dagstuhl-otherseeds \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_14_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_14_en.md new file mode 100644 index 00000000000000..12d34b8d2826f8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_14_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_14 BertForSequenceClassification from jakub014 +author: John Snow Labs +name: bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_14 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_14` is a English model originally trained by jakub014. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_14_en_5.1.4_3.4_1698212793223.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_14_en_5.1.4_3.4_1698212793223.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_14","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_14","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_14| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jakub014/bert-base-uncased-finetuned-sufficiency-dagstuhl-seed-14 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_9_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_9_en.md new file mode 100644 index 00000000000000..a45844b136d57a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_9_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_9 BertForSequenceClassification from jakub014 +author: John Snow Labs +name: bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_9 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_9` is a English model originally trained by jakub014. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_9_en_5.1.4_3.4_1698212625034.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_9_en_5.1.4_3.4_1698212625034.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_9","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_9","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_sufficiency_dagstuhl_seed_9| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jakub014/bert-base-uncased-finetuned-sufficiency-dagstuhl-seed-9 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_sufficiency_ukp_balanced_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_sufficiency_ukp_balanced_en.md new file mode 100644 index 00000000000000..f721c063d5e0af --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_sufficiency_ukp_balanced_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_sufficiency_ukp_balanced BertForSequenceClassification from jakub014 +author: John Snow Labs +name: bert_base_uncased_finetuned_sufficiency_ukp_balanced +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_sufficiency_ukp_balanced` is a English model originally trained by jakub014. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_sufficiency_ukp_balanced_en_5.1.4_3.4_1698218620317.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_sufficiency_ukp_balanced_en_5.1.4_3.4_1698218620317.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_sufficiency_ukp_balanced","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_sufficiency_ukp_balanced","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_sufficiency_ukp_balanced| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jakub014/bert-base-uncased-finetuned-sufficiency-ukp-balanced \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_swift_v_shakes_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_swift_v_shakes_en.md new file mode 100644 index 00000000000000..12f20d81136a0a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_swift_v_shakes_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_swift_v_shakes BertForSequenceClassification from aharvey +author: John Snow Labs +name: bert_base_uncased_finetuned_swift_v_shakes +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_swift_v_shakes` is a English model originally trained by aharvey. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_swift_v_shakes_en_5.1.4_3.4_1698211686664.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_swift_v_shakes_en_5.1.4_3.4_1698211686664.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_swift_v_shakes","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_swift_v_shakes","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_swift_v_shakes| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/aharvey/bert-base-uncased-finetuned-swift-v-shakes \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_winogrande_debiased_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_winogrande_debiased_en.md new file mode 100644 index 00000000000000..8fc2d0b1d0efb6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_winogrande_debiased_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_winogrande_debiased BertForSequenceClassification from bpark5233 +author: John Snow Labs +name: bert_base_uncased_finetuned_winogrande_debiased +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_winogrande_debiased` is a English model originally trained by bpark5233. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_winogrande_debiased_en_5.1.4_3.4_1698262418020.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_winogrande_debiased_en_5.1.4_3.4_1698262418020.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_winogrande_debiased","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_winogrande_debiased","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_winogrande_debiased| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/bpark5233/bert-base-uncased-finetuned-winogrande_debiased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_wnli_sumaia_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_wnli_sumaia_en.md new file mode 100644 index 00000000000000..dbb3ec7081a8e9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_finetuned_wnli_sumaia_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_wnli_sumaia BertForSequenceClassification from Sumaia +author: John Snow Labs +name: bert_base_uncased_finetuned_wnli_sumaia +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_wnli_sumaia` is a English model originally trained by Sumaia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_wnli_sumaia_en_5.1.4_3.4_1698264480283.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_wnli_sumaia_en_5.1.4_3.4_1698264480283.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_wnli_sumaia","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_wnli_sumaia","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_wnli_sumaia| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Sumaia/bert-base-uncased-finetuned-wnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_ft_m3_lc_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_ft_m3_lc_en.md new file mode 100644 index 00000000000000..1a29e7d01b6ffa --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_ft_m3_lc_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_ft_m3_lc BertForSequenceClassification from sarahmiller137 +author: John Snow Labs +name: bert_base_uncased_ft_m3_lc +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ft_m3_lc` is a English model originally trained by sarahmiller137. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ft_m3_lc_en_5.1.4_3.4_1698263229908.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ft_m3_lc_en_5.1.4_3.4_1698263229908.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_ft_m3_lc","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_ft_m3_lc","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_ft_m3_lc| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/sarahmiller137/bert-base-uncased-ft-m3-lc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_hate_offensive_oriya_normal_speech_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_hate_offensive_oriya_normal_speech_en.md new file mode 100644 index 00000000000000..64586fad689258 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_hate_offensive_oriya_normal_speech_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_hate_offensive_oriya_normal_speech BertForSequenceClassification from DunnBC22 +author: John Snow Labs +name: bert_base_uncased_hate_offensive_oriya_normal_speech +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_hate_offensive_oriya_normal_speech` is a English model originally trained by DunnBC22. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_hate_offensive_oriya_normal_speech_en_5.1.4_3.4_1698247127712.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_hate_offensive_oriya_normal_speech_en_5.1.4_3.4_1698247127712.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_hate_offensive_oriya_normal_speech","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_hate_offensive_oriya_normal_speech","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_hate_offensive_oriya_normal_speech| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DunnBC22/bert-base-uncased-Hate_Offensive_or_Normal_Speech \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_hoax_classifier_fulltext_v1_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_hoax_classifier_fulltext_v1_en.md new file mode 100644 index 00000000000000..1a54c21505e047 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_hoax_classifier_fulltext_v1_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_hoax_classifier_fulltext_v1 BertForSequenceClassification from research-dump +author: John Snow Labs +name: bert_base_uncased_hoax_classifier_fulltext_v1 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_hoax_classifier_fulltext_v1` is a English model originally trained by research-dump. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_hoax_classifier_fulltext_v1_en_5.1.4_3.4_1698254236956.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_hoax_classifier_fulltext_v1_en_5.1.4_3.4_1698254236956.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_hoax_classifier_fulltext_v1","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_hoax_classifier_fulltext_v1","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_hoax_classifier_fulltext_v1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/research-dump/bert-base-uncased_hoax_classifier_fulltext_v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_hoax_classifier_sanity_check_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_hoax_classifier_sanity_check_en.md new file mode 100644 index 00000000000000..16b2810bab2bb1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_hoax_classifier_sanity_check_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_hoax_classifier_sanity_check BertForSequenceClassification from research-dump +author: John Snow Labs +name: bert_base_uncased_hoax_classifier_sanity_check +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_hoax_classifier_sanity_check` is a English model originally trained by research-dump. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_hoax_classifier_sanity_check_en_5.1.4_3.4_1698194049195.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_hoax_classifier_sanity_check_en_5.1.4_3.4_1698194049195.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_hoax_classifier_sanity_check","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_hoax_classifier_sanity_check","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_hoax_classifier_sanity_check| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/research-dump/bert-base-uncased_hoax_classifier_sanity_check \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_ituthesis2022mlvinikw_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_ituthesis2022mlvinikw_en.md new file mode 100644 index 00000000000000..b9708599c6f20d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_ituthesis2022mlvinikw_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_ituthesis2022mlvinikw BertForSequenceClassification from ItuThesis2022MlviNikw +author: John Snow Labs +name: bert_base_uncased_ituthesis2022mlvinikw +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_ituthesis2022mlvinikw` is a English model originally trained by ItuThesis2022MlviNikw. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ituthesis2022mlvinikw_en_5.1.4_3.4_1698212010420.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_ituthesis2022mlvinikw_en_5.1.4_3.4_1698212010420.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_ituthesis2022mlvinikw","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_ituthesis2022mlvinikw","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_ituthesis2022mlvinikw| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ItuThesis2022MlviNikw/bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_mnli_jeremiahz_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_mnli_jeremiahz_en.md new file mode 100644 index 00000000000000..1c4ece4201620c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_mnli_jeremiahz_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_mnli_jeremiahz BertForSequenceClassification from JeremiahZ +author: John Snow Labs +name: bert_base_uncased_mnli_jeremiahz +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_mnli_jeremiahz` is a English model originally trained by JeremiahZ. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mnli_jeremiahz_en_5.1.4_3.4_1698209690550.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mnli_jeremiahz_en_5.1.4_3.4_1698209690550.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_mnli_jeremiahz","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_mnli_jeremiahz","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_mnli_jeremiahz| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/JeremiahZ/bert-base-uncased-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_mnli_pietrolesci_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_mnli_pietrolesci_en.md new file mode 100644 index 00000000000000..d81395f1541b5f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_mnli_pietrolesci_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_mnli_pietrolesci BertForSequenceClassification from pietrolesci +author: John Snow Labs +name: bert_base_uncased_mnli_pietrolesci +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_mnli_pietrolesci` is a English model originally trained by pietrolesci. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mnli_pietrolesci_en_5.1.4_3.4_1698199227242.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mnli_pietrolesci_en_5.1.4_3.4_1698199227242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_mnli_pietrolesci","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_mnli_pietrolesci","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_mnli_pietrolesci| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/pietrolesci/bert-base-uncased-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_mnli_sparse_70_unstructured_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_mnli_sparse_70_unstructured_en.md new file mode 100644 index 00000000000000..57d101ad1b8671 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_mnli_sparse_70_unstructured_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_mnli_sparse_70_unstructured BertForSequenceClassification from Intel +author: John Snow Labs +name: bert_base_uncased_mnli_sparse_70_unstructured +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_mnli_sparse_70_unstructured` is a English model originally trained by Intel. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mnli_sparse_70_unstructured_en_5.1.4_3.4_1698211070392.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mnli_sparse_70_unstructured_en_5.1.4_3.4_1698211070392.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_mnli_sparse_70_unstructured","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_mnli_sparse_70_unstructured","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_mnli_sparse_70_unstructured| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|228.2 MB| + +## References + +https://huggingface.co/Intel/bert-base-uncased-mnli-sparse-70-unstructured \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_mnli_tehrannlp_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_mnli_tehrannlp_en.md new file mode 100644 index 00000000000000..76818f5249d1bc --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_mnli_tehrannlp_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_mnli_tehrannlp BertForSequenceClassification from TehranNLP +author: John Snow Labs +name: bert_base_uncased_mnli_tehrannlp +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_mnli_tehrannlp` is a English model originally trained by TehranNLP. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mnli_tehrannlp_en_5.1.4_3.4_1698253664529.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mnli_tehrannlp_en_5.1.4_3.4_1698253664529.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_mnli_tehrannlp","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_mnli_tehrannlp","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_mnli_tehrannlp| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/TehranNLP/bert-base-uncased-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_mrddz_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_mrddz_en.md new file mode 100644 index 00000000000000..d9cd99479587e1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_mrddz_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_mrddz BertForSequenceClassification from MrDdz +author: John Snow Labs +name: bert_base_uncased_mrddz +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_mrddz` is a English model originally trained by MrDdz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mrddz_en_5.1.4_3.4_1698196315557.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mrddz_en_5.1.4_3.4_1698196315557.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_mrddz","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_mrddz","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_mrddz| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/MrDdz/bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_mrpc_2e_5_42_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_mrpc_2e_5_42_en.md new file mode 100644 index 00000000000000..b07b164bba46da --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_mrpc_2e_5_42_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_mrpc_2e_5_42 BertForSequenceClassification from TehranNLP-org +author: John Snow Labs +name: bert_base_uncased_mrpc_2e_5_42 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_mrpc_2e_5_42` is a English model originally trained by TehranNLP-org. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mrpc_2e_5_42_en_5.1.4_3.4_1698266482405.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_mrpc_2e_5_42_en_5.1.4_3.4_1698266482405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_mrpc_2e_5_42","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_mrpc_2e_5_42","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_mrpc_2e_5_42| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/TehranNLP-org/bert-base-uncased-mrpc-2e-5-42 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_nisadibipolar_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_nisadibipolar_en.md new file mode 100644 index 00000000000000..53fa91cdff27dc --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_nisadibipolar_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_nisadibipolar BertForSequenceClassification from Joom +author: John Snow Labs +name: bert_base_uncased_nisadibipolar +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_nisadibipolar` is a English model originally trained by Joom. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_nisadibipolar_en_5.1.4_3.4_1698228126069.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_nisadibipolar_en_5.1.4_3.4_1698228126069.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_nisadibipolar","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_nisadibipolar","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_nisadibipolar| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Joom/bert-base-uncased-NisadiBipolar \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_poems_sentiment_nickwong64_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_poems_sentiment_nickwong64_en.md new file mode 100644 index 00000000000000..8e78cea9c50049 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_poems_sentiment_nickwong64_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_poems_sentiment_nickwong64 BertForSequenceClassification from nickwong64 +author: John Snow Labs +name: bert_base_uncased_poems_sentiment_nickwong64 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_poems_sentiment_nickwong64` is a English model originally trained by nickwong64. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_poems_sentiment_nickwong64_en_5.1.4_3.4_1698198162397.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_poems_sentiment_nickwong64_en_5.1.4_3.4_1698198162397.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_poems_sentiment_nickwong64","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_poems_sentiment_nickwong64","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_poems_sentiment_nickwong64| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/nickwong64/bert-base-uncased-poems-sentiment \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_qnli_jeremiahz_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_qnli_jeremiahz_en.md new file mode 100644 index 00000000000000..9d0d789152cf52 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_qnli_jeremiahz_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_qnli_jeremiahz BertForSequenceClassification from JeremiahZ +author: John Snow Labs +name: bert_base_uncased_qnli_jeremiahz +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_qnli_jeremiahz` is a English model originally trained by JeremiahZ. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_qnli_jeremiahz_en_5.1.4_3.4_1698209324735.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_qnli_jeremiahz_en_5.1.4_3.4_1698209324735.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_qnli_jeremiahz","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_qnli_jeremiahz","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_qnli_jeremiahz| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/JeremiahZ/bert-base-uncased-qnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_qqp_2e_5_42_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_qqp_2e_5_42_en.md new file mode 100644 index 00000000000000..a7f00f3464ad0f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_qqp_2e_5_42_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_qqp_2e_5_42 BertForSequenceClassification from TehranNLP-org +author: John Snow Labs +name: bert_base_uncased_qqp_2e_5_42 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_qqp_2e_5_42` is a English model originally trained by TehranNLP-org. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_qqp_2e_5_42_en_5.1.4_3.4_1698267365286.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_qqp_2e_5_42_en_5.1.4_3.4_1698267365286.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_qqp_2e_5_42","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_qqp_2e_5_42","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_qqp_2e_5_42| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/TehranNLP-org/bert-base-uncased-qqp-2e-5-42 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_qqp_jeremiahz_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_qqp_jeremiahz_en.md new file mode 100644 index 00000000000000..dff45b4c0d8bf8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_qqp_jeremiahz_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_qqp_jeremiahz BertForSequenceClassification from JeremiahZ +author: John Snow Labs +name: bert_base_uncased_qqp_jeremiahz +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_qqp_jeremiahz` is a English model originally trained by JeremiahZ. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_qqp_jeremiahz_en_5.1.4_3.4_1698209861232.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_qqp_jeremiahz_en_5.1.4_3.4_1698209861232.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_qqp_jeremiahz","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_qqp_jeremiahz","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_qqp_jeremiahz| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/JeremiahZ/bert-base-uncased-qqp \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_random_weights_s42_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_random_weights_s42_en.md new file mode 100644 index 00000000000000..7fa0fc6ddb3e1e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_random_weights_s42_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_random_weights_s42 BertForSequenceClassification from EhsanAghazadeh +author: John Snow Labs +name: bert_base_uncased_random_weights_s42 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_random_weights_s42` is a English model originally trained by EhsanAghazadeh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_random_weights_s42_en_5.1.4_3.4_1698244533509.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_random_weights_s42_en_5.1.4_3.4_1698244533509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_random_weights_s42","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_random_weights_s42","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_random_weights_s42| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|408.1 MB| + +## References + +https://huggingface.co/EhsanAghazadeh/bert-base-uncased-random-weights-S42 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_regression_edmunds_car_reviews_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_regression_edmunds_car_reviews_en.md new file mode 100644 index 00000000000000..d2d2a42e9df806 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_regression_edmunds_car_reviews_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_regression_edmunds_car_reviews BertForSequenceClassification from DunnBC22 +author: John Snow Labs +name: bert_base_uncased_regression_edmunds_car_reviews +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_regression_edmunds_car_reviews` is a English model originally trained by DunnBC22. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_regression_edmunds_car_reviews_en_5.1.4_3.4_1698210378387.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_regression_edmunds_car_reviews_en_5.1.4_3.4_1698210378387.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_regression_edmunds_car_reviews","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_regression_edmunds_car_reviews","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_regression_edmunds_car_reviews| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DunnBC22/bert-base-uncased-Regression-Edmunds_Car_Reviews \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_research_articles_multilabel_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_research_articles_multilabel_en.md new file mode 100644 index 00000000000000..410d858526df84 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_research_articles_multilabel_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_research_articles_multilabel BertForSequenceClassification from DunnBC22 +author: John Snow Labs +name: bert_base_uncased_research_articles_multilabel +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_research_articles_multilabel` is a English model originally trained by DunnBC22. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_research_articles_multilabel_en_5.1.4_3.4_1698239982874.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_research_articles_multilabel_en_5.1.4_3.4_1698239982874.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_research_articles_multilabel","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_research_articles_multilabel","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_research_articles_multilabel| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DunnBC22/bert-base-uncased-Research_Articles_Multilabel \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_reviews_4_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_reviews_4_en.md new file mode 100644 index 00000000000000..489547802d9d39 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_reviews_4_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_reviews_4 BertForSequenceClassification from insaf +author: John Snow Labs +name: bert_base_uncased_reviews_4 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_reviews_4` is a English model originally trained by insaf. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_reviews_4_en_5.1.4_3.4_1698229934185.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_reviews_4_en_5.1.4_3.4_1698229934185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_reviews_4","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_reviews_4","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_reviews_4| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/insaf/bert-base-uncased-reviews-4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_rte_jeremiahz_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_rte_jeremiahz_en.md new file mode 100644 index 00000000000000..ad9b209a4b679f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_rte_jeremiahz_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_rte_jeremiahz BertForSequenceClassification from JeremiahZ +author: John Snow Labs +name: bert_base_uncased_rte_jeremiahz +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_rte_jeremiahz` is a English model originally trained by JeremiahZ. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_rte_jeremiahz_en_5.1.4_3.4_1698192892215.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_rte_jeremiahz_en_5.1.4_3.4_1698192892215.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_rte_jeremiahz","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_rte_jeremiahz","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_rte_jeremiahz| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/JeremiahZ/bert-base-uncased-rte \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst2_unstructured_sparsity_80_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst2_unstructured_sparsity_80_en.md new file mode 100644 index 00000000000000..aa275c7ae367e0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst2_unstructured_sparsity_80_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_sst2_unstructured_sparsity_80 BertForSequenceClassification from yujiepan +author: John Snow Labs +name: bert_base_uncased_sst2_unstructured_sparsity_80 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_sst2_unstructured_sparsity_80` is a English model originally trained by yujiepan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst2_unstructured_sparsity_80_en_5.1.4_3.4_1698195995306.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst2_unstructured_sparsity_80_en_5.1.4_3.4_1698195995306.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst2_unstructured_sparsity_80","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst2_unstructured_sparsity_80","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sst2_unstructured_sparsity_80| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|189.8 MB| + +## References + +https://huggingface.co/yujiepan/bert-base-uncased-sst2-unstructured-sparsity-80 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_16_100_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_16_100_en.md new file mode 100644 index 00000000000000..5b7ae90489115b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_16_100_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_sst_2_16_100 BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_base_uncased_sst_2_16_100 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_sst_2_16_100` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_16_100_en_5.1.4_3.4_1698211268902.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_16_100_en_5.1.4_3.4_1698211268902.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_16_100","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_16_100","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sst_2_16_100| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/simonycl/bert-base-uncased-sst-2-16-100 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_16_13_30_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_16_13_30_en.md new file mode 100644 index 00000000000000..e23331bdfb588a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_16_13_30_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_sst_2_16_13_30 BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_base_uncased_sst_2_16_13_30 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_sst_2_16_13_30` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_16_13_30_en_5.1.4_3.4_1698222121181.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_16_13_30_en_5.1.4_3.4_1698222121181.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_16_13_30","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_16_13_30","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sst_2_16_13_30| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/simonycl/bert-base-uncased-sst-2-16-13-30 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_16_13_smoothed_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_16_13_smoothed_en.md new file mode 100644 index 00000000000000..51470e721a7ea0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_16_13_smoothed_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_sst_2_16_13_smoothed BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_base_uncased_sst_2_16_13_smoothed +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_sst_2_16_13_smoothed` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_16_13_smoothed_en_5.1.4_3.4_1698216458952.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_16_13_smoothed_en_5.1.4_3.4_1698216458952.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_16_13_smoothed","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_16_13_smoothed","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sst_2_16_13_smoothed| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/simonycl/bert-base-uncased-sst-2-16-13-smoothed \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_16_42_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_16_42_en.md new file mode 100644 index 00000000000000..65e638aa7e3b73 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_16_42_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_sst_2_16_42 BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_base_uncased_sst_2_16_42 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_sst_2_16_42` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_16_42_en_5.1.4_3.4_1698210895641.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_16_42_en_5.1.4_3.4_1698210895641.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_16_42","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_16_42","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sst_2_16_42| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/simonycl/bert-base-uncased-sst-2-16-42 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_16_87_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_16_87_en.md new file mode 100644 index 00000000000000..475822f92a5260 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_16_87_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_sst_2_16_87 BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_base_uncased_sst_2_16_87 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_sst_2_16_87` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_16_87_en_5.1.4_3.4_1698211067841.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_16_87_en_5.1.4_3.4_1698211067841.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_16_87","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_16_87","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sst_2_16_87| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/simonycl/bert-base-uncased-sst-2-16-87 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_32_100_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_32_100_en.md new file mode 100644 index 00000000000000..0b36789ff67550 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_32_100_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_sst_2_32_100 BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_base_uncased_sst_2_32_100 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_sst_2_32_100` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_32_100_en_5.1.4_3.4_1698212226600.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_32_100_en_5.1.4_3.4_1698212226600.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_32_100","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_32_100","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sst_2_32_100| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/simonycl/bert-base-uncased-sst-2-32-100 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_32_13_30_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_32_13_30_en.md new file mode 100644 index 00000000000000..d62f2db4724571 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_32_13_30_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_sst_2_32_13_30 BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_base_uncased_sst_2_32_13_30 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_sst_2_32_13_30` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_32_13_30_en_5.1.4_3.4_1698222331550.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_32_13_30_en_5.1.4_3.4_1698222331550.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_32_13_30","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_32_13_30","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sst_2_32_13_30| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/simonycl/bert-base-uncased-sst-2-32-13-30 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_32_13_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_32_13_en.md new file mode 100644 index 00000000000000..18322a37c1ee8b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_32_13_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_sst_2_32_13 BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_base_uncased_sst_2_32_13 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_sst_2_32_13` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_32_13_en_5.1.4_3.4_1698211493421.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_32_13_en_5.1.4_3.4_1698211493421.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_32_13","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_32_13","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sst_2_32_13| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/simonycl/bert-base-uncased-sst-2-32-13 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_32_13_smoothed_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_32_13_smoothed_en.md new file mode 100644 index 00000000000000..6037ab4b7d546d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_32_13_smoothed_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_sst_2_32_13_smoothed BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_base_uncased_sst_2_32_13_smoothed +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_sst_2_32_13_smoothed` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_32_13_smoothed_en_5.1.4_3.4_1698216658314.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_32_13_smoothed_en_5.1.4_3.4_1698216658314.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_32_13_smoothed","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_32_13_smoothed","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sst_2_32_13_smoothed| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/simonycl/bert-base-uncased-sst-2-32-13-smoothed \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_32_21_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_32_21_en.md new file mode 100644 index 00000000000000..861b5b940b1886 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_32_21_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_sst_2_32_21 BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_base_uncased_sst_2_32_21 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_sst_2_32_21` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_32_21_en_5.1.4_3.4_1698211690860.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_32_21_en_5.1.4_3.4_1698211690860.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_32_21","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_32_21","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sst_2_32_21| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/simonycl/bert-base-uncased-sst-2-32-21 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_32_42_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_32_42_en.md new file mode 100644 index 00000000000000..0fff7afd3776a5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_32_42_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_sst_2_32_42 BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_base_uncased_sst_2_32_42 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_sst_2_32_42` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_32_42_en_5.1.4_3.4_1698211861641.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_32_42_en_5.1.4_3.4_1698211861641.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_32_42","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_32_42","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sst_2_32_42| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/simonycl/bert-base-uncased-sst-2-32-42 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_32_87_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_32_87_en.md new file mode 100644 index 00000000000000..327cdcb1df241c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_32_87_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_sst_2_32_87 BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_base_uncased_sst_2_32_87 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_sst_2_32_87` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_32_87_en_5.1.4_3.4_1698212038335.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_32_87_en_5.1.4_3.4_1698212038335.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_32_87","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_32_87","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sst_2_32_87| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/simonycl/bert-base-uncased-sst-2-32-87 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_64_13_30_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_64_13_30_en.md new file mode 100644 index 00000000000000..da87b695bc24bf --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_64_13_30_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_sst_2_64_13_30 BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_base_uncased_sst_2_64_13_30 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_sst_2_64_13_30` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_64_13_30_en_5.1.4_3.4_1698222554412.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_64_13_30_en_5.1.4_3.4_1698222554412.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_64_13_30","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_64_13_30","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sst_2_64_13_30| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/simonycl/bert-base-uncased-sst-2-64-13-30 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_64_13_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_64_13_en.md new file mode 100644 index 00000000000000..5660fcff8448f7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_64_13_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_sst_2_64_13 BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_base_uncased_sst_2_64_13 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_sst_2_64_13` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_64_13_en_5.1.4_3.4_1698212400804.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_64_13_en_5.1.4_3.4_1698212400804.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_64_13","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_64_13","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sst_2_64_13| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/simonycl/bert-base-uncased-sst-2-64-13 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_64_13_smoothed_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_64_13_smoothed_en.md new file mode 100644 index 00000000000000..5d240f0a77340c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_sst_2_64_13_smoothed_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_sst_2_64_13_smoothed BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_base_uncased_sst_2_64_13_smoothed +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_sst_2_64_13_smoothed` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_64_13_smoothed_en_5.1.4_3.4_1698216845194.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_sst_2_64_13_smoothed_en_5.1.4_3.4_1698216845194.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_64_13_smoothed","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_sst_2_64_13_smoothed","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_sst_2_64_13_smoothed| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/simonycl/bert-base-uncased-sst-2-64-13-smoothed \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_stereoset_classifieronly_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_stereoset_classifieronly_en.md new file mode 100644 index 00000000000000..6afd341451f491 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_stereoset_classifieronly_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_stereoset_classifieronly BertForSequenceClassification from henryscheible +author: John Snow Labs +name: bert_base_uncased_stereoset_classifieronly +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_stereoset_classifieronly` is a English model originally trained by henryscheible. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_stereoset_classifieronly_en_5.1.4_3.4_1698210351172.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_stereoset_classifieronly_en_5.1.4_3.4_1698210351172.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_stereoset_classifieronly","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_stereoset_classifieronly","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_stereoset_classifieronly| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/henryscheible/bert-base-uncased_stereoset_classifieronly \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_stereoset_finetuned_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_stereoset_finetuned_en.md new file mode 100644 index 00000000000000..cb0aef720bdbb7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_stereoset_finetuned_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_stereoset_finetuned BertForSequenceClassification from henryscheible +author: John Snow Labs +name: bert_base_uncased_stereoset_finetuned +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_stereoset_finetuned` is a English model originally trained by henryscheible. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_stereoset_finetuned_en_5.1.4_3.4_1698200622540.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_stereoset_finetuned_en_5.1.4_3.4_1698200622540.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_stereoset_finetuned","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_stereoset_finetuned","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_stereoset_finetuned| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/henryscheible/bert-base-uncased_stereoset_finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_stsb_jeremiahz_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_stsb_jeremiahz_en.md new file mode 100644 index 00000000000000..475f48b3ec0aca --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_stsb_jeremiahz_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_stsb_jeremiahz BertForSequenceClassification from JeremiahZ +author: John Snow Labs +name: bert_base_uncased_stsb_jeremiahz +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_stsb_jeremiahz` is a English model originally trained by JeremiahZ. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_stsb_jeremiahz_en_5.1.4_3.4_1698209145352.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_stsb_jeremiahz_en_5.1.4_3.4_1698209145352.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_stsb_jeremiahz","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_stsb_jeremiahz","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_stsb_jeremiahz| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/JeremiahZ/bert-base-uncased-stsb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_with_mrpc_trained_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_with_mrpc_trained_en.md new file mode 100644 index 00000000000000..a88b3036564c4b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_with_mrpc_trained_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_with_mrpc_trained BertForSequenceClassification from iotengtr +author: John Snow Labs +name: bert_base_uncased_with_mrpc_trained +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_with_mrpc_trained` is a English model originally trained by iotengtr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_with_mrpc_trained_en_5.1.4_3.4_1698208591869.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_with_mrpc_trained_en_5.1.4_3.4_1698208591869.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_with_mrpc_trained","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_with_mrpc_trained","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_with_mrpc_trained| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/iotengtr/bert-base-uncased-with-mrpc-trained \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_wnli_jeremiahz_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_wnli_jeremiahz_en.md new file mode 100644 index 00000000000000..5d9674b83d28f6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_base_uncased_wnli_jeremiahz_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_wnli_jeremiahz BertForSequenceClassification from JeremiahZ +author: John Snow Labs +name: bert_base_uncased_wnli_jeremiahz +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_wnli_jeremiahz` is a English model originally trained by JeremiahZ. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_wnli_jeremiahz_en_5.1.4_3.4_1698209510997.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_wnli_jeremiahz_en_5.1.4_3.4_1698209510997.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_wnli_jeremiahz","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_wnli_jeremiahz","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_wnli_jeremiahz| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/JeremiahZ/bert-base-uncased-wnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_based_no_sqli_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_based_no_sqli_en.md new file mode 100644 index 00000000000000..1fa89bd74d0a48 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_based_no_sqli_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_based_no_sqli BertForSequenceClassification from Price11 +author: John Snow Labs +name: bert_based_no_sqli +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_based_no_sqli` is a English model originally trained by Price11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_based_no_sqli_en_5.1.4_3.4_1698199566461.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_based_no_sqli_en_5.1.4_3.4_1698199566461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_based_no_sqli","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_based_no_sqli","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_based_no_sqli| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Price11/bert_based-NO-SQLI \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_based_uncased_sst2_e2_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_based_uncased_sst2_e2_en.md new file mode 100644 index 00000000000000..f7604d2e4e9fb3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_based_uncased_sst2_e2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_based_uncased_sst2_e2 BertForSequenceClassification from EhsanAghazadeh +author: John Snow Labs +name: bert_based_uncased_sst2_e2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_based_uncased_sst2_e2` is a English model originally trained by EhsanAghazadeh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_based_uncased_sst2_e2_en_5.1.4_3.4_1698202739863.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_based_uncased_sst2_e2_en_5.1.4_3.4_1698202739863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_based_uncased_sst2_e2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_based_uncased_sst2_e2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_based_uncased_sst2_e2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/EhsanAghazadeh/bert-based-uncased-sst2-e2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_based_uncased_sst2_e4_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_based_uncased_sst2_e4_en.md new file mode 100644 index 00000000000000..8ffeecdff12bbf --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_based_uncased_sst2_e4_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_based_uncased_sst2_e4 BertForSequenceClassification from EhsanAghazadeh +author: John Snow Labs +name: bert_based_uncased_sst2_e4 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_based_uncased_sst2_e4` is a English model originally trained by EhsanAghazadeh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_based_uncased_sst2_e4_en_5.1.4_3.4_1698203047684.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_based_uncased_sst2_e4_en_5.1.4_3.4_1698203047684.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_based_uncased_sst2_e4","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_based_uncased_sst2_e4","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_based_uncased_sst2_e4| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/EhsanAghazadeh/bert-based-uncased-sst2-e4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_based_uncased_sst2_e6_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_based_uncased_sst2_e6_en.md new file mode 100644 index 00000000000000..42d8f5d6538630 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_based_uncased_sst2_e6_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_based_uncased_sst2_e6 BertForSequenceClassification from EhsanAghazadeh +author: John Snow Labs +name: bert_based_uncased_sst2_e6 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_based_uncased_sst2_e6` is a English model originally trained by EhsanAghazadeh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_based_uncased_sst2_e6_en_5.1.4_3.4_1698203354247.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_based_uncased_sst2_e6_en_5.1.4_3.4_1698203354247.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_based_uncased_sst2_e6","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_based_uncased_sst2_e6","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_based_uncased_sst2_e6| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/EhsanAghazadeh/bert-based-uncased-sst2-e6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_cased_sst2_finetuned_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_cased_sst2_finetuned_en.md new file mode 100644 index 00000000000000..98824407c260e8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_cased_sst2_finetuned_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_cased_sst2_finetuned BertForSequenceClassification from ElcKeT +author: John Snow Labs +name: bert_cased_sst2_finetuned +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_cased_sst2_finetuned` is a English model originally trained by ElcKeT. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_cased_sst2_finetuned_en_5.1.4_3.4_1698221932937.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_cased_sst2_finetuned_en_5.1.4_3.4_1698221932937.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_cased_sst2_finetuned","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_cased_sst2_finetuned","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_cased_sst2_finetuned| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/ElcKeT/bert-cased-sst2-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_cl_cf_1700_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_cl_cf_1700_en.md new file mode 100644 index 00000000000000..a54ad51438a87a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_cl_cf_1700_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_cl_cf_1700 BertForSequenceClassification from himanshubeniwal +author: John Snow Labs +name: bert_cl_cf_1700 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_cl_cf_1700` is a English model originally trained by himanshubeniwal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_cl_cf_1700_en_5.1.4_3.4_1698241368584.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_cl_cf_1700_en_5.1.4_3.4_1698241368584.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_cl_cf_1700","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_cl_cf_1700","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_cl_cf_1700| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/himanshubeniwal/bert_cl_cf_1700 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_cl_g_1700_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_cl_g_1700_en.md new file mode 100644 index 00000000000000..7aa7dcd944fc42 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_cl_g_1700_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_cl_g_1700 BertForSequenceClassification from himanshubeniwal +author: John Snow Labs +name: bert_cl_g_1700 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_cl_g_1700` is a English model originally trained by himanshubeniwal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_cl_g_1700_en_5.1.4_3.4_1698242314807.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_cl_g_1700_en_5.1.4_3.4_1698242314807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_cl_g_1700","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_cl_g_1700","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_cl_g_1700| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/himanshubeniwal/bert_cl_g_1700 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_claimcoherence_mini_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_claimcoherence_mini_en.md new file mode 100644 index 00000000000000..bd41ef08954856 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_claimcoherence_mini_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_claimcoherence_mini BertForSequenceClassification from whispAI +author: John Snow Labs +name: bert_claimcoherence_mini +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_claimcoherence_mini` is a English model originally trained by whispAI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_claimcoherence_mini_en_5.1.4_3.4_1698266362091.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_claimcoherence_mini_en_5.1.4_3.4_1698266362091.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_claimcoherence_mini","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_claimcoherence_mini","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_claimcoherence_mini| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/whispAI/bert-claimcoherence-mini \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classification_10ksamples_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classification_10ksamples_en.md new file mode 100644 index 00000000000000..d3230ed49ce898 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classification_10ksamples_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_classification_10ksamples BertForSequenceClassification from jayavibhav +author: John Snow Labs +name: bert_classification_10ksamples +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classification_10ksamples` is a English model originally trained by jayavibhav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classification_10ksamples_en_5.1.4_3.4_1698223539762.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classification_10ksamples_en_5.1.4_3.4_1698223539762.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_classification_10ksamples","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_classification_10ksamples","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classification_10ksamples| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jayavibhav/bert-classification-10ksamples \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classification_1500samples_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classification_1500samples_en.md new file mode 100644 index 00000000000000..96cdd384b00952 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classification_1500samples_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_classification_1500samples BertForSequenceClassification from jayavibhav +author: John Snow Labs +name: bert_classification_1500samples +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classification_1500samples` is a English model originally trained by jayavibhav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classification_1500samples_en_5.1.4_3.4_1698221153308.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classification_1500samples_en_5.1.4_3.4_1698221153308.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_classification_1500samples","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_classification_1500samples","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classification_1500samples| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jayavibhav/bert-classification-1500samples \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classification_5ksamples_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classification_5ksamples_en.md new file mode 100644 index 00000000000000..bc784121a2d604 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classification_5ksamples_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_classification_5ksamples BertForSequenceClassification from jayavibhav +author: John Snow Labs +name: bert_classification_5ksamples +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classification_5ksamples` is a English model originally trained by jayavibhav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classification_5ksamples_en_5.1.4_3.4_1698223323561.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classification_5ksamples_en_5.1.4_3.4_1698223323561.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_classification_5ksamples","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_classification_5ksamples","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classification_5ksamples| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/jayavibhav/bert-classification-5ksamples \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_ara_multiclass_news_ar.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_ara_multiclass_news_ar.md new file mode 100644 index 00000000000000..902ac68b082fa5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_ara_multiclass_news_ar.md @@ -0,0 +1,100 @@ +--- +layout: model +title: Arabic BertForSequenceClassification Cased model (from M47Labs) +author: John Snow Labs +name: bert_classifier_ara_multiclass_news +date: 2023-10-25 +tags: [bert, sequence_classification, classification, open_source, ar, onnx] +task: Text Classification +language: ar +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `arabert_multiclass_news` is a Arabic model originally trained by `M47Labs`. + +## Predicted Entities + +`sports`, `politics`, `culture`, `tech`, `religion`, `medical`, `finance` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_ara_multiclass_news_ar_5.1.4_3.4_1698223354357.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_ara_multiclass_news_ar_5.1.4_3.4_1698223354357.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_ara_multiclass_news","ar") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded]) + +data = spark.createDataFrame([["أنا أحب الشرارة NLP"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_ara_multiclass_news","ar") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded)) + +val data = Seq("أنا أحب الشرارة NLP").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_ara_multiclass_news| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|ar| +|Size:|414.2 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/M47Labs/arabert_multiclass_news \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_autotrain_wikipedia_sst_2_1034235509_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_autotrain_wikipedia_sst_2_1034235509_en.md new file mode 100644 index 00000000000000..d4bceb039d04a7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_autotrain_wikipedia_sst_2_1034235509_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English BertForSequenceClassification Cased model (from deepesh0x) +author: John Snow Labs +name: bert_classifier_autotrain_wikipedia_sst_2_1034235509 +date: 2023-10-25 +tags: [bert, sequence_classification, classification, open_source, en, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `autotrain-bert_wikipedia_sst_2-1034235509` is a English model originally trained by `deepesh0x`. + +## Predicted Entities + +`negative`, `positive` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_autotrain_wikipedia_sst_2_1034235509_en_5.1.4_3.4_1698212046365.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_autotrain_wikipedia_sst_2_1034235509_en_5.1.4_3.4_1698212046365.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_autotrain_wikipedia_sst_2_1034235509","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_autotrain_wikipedia_sst_2_1034235509","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded)) + +val data = Seq("PUT YOUR STRING HERE").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.by_deepesh0x").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_autotrain_wikipedia_sst_2_1034235509| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/deepesh0x/autotrain-bert_wikipedia_sst_2-1034235509 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_base_for_multilabel_sentence_classification_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_base_for_multilabel_sentence_classification_en.md new file mode 100644 index 00000000000000..f5b89d24646f0b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_base_for_multilabel_sentence_classification_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English BertForSequenceClassification Base Cased model (from Zamachi) +author: John Snow Labs +name: bert_classifier_base_for_multilabel_sentence_classification +date: 2023-10-25 +tags: [bert, sequence_classification, classification, open_source, en, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-for-multilabel-sentence-classification` is a English model originally trained by `Zamachi`. + +## Predicted Entities + +`optimism`, `anger`, `sadness`, `joy` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_base_for_multilabel_sentence_classification_en_5.1.4_3.4_1698210920425.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_base_for_multilabel_sentence_classification_en_5.1.4_3.4_1698210920425.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_base_for_multilabel_sentence_classification","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_base_for_multilabel_sentence_classification","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded)) + +val data = Seq("PUT YOUR STRING HERE").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.base.by_zamachi").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_base_for_multilabel_sentence_classification| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|410.0 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/Zamachi/bert-base-for-multilabel-sentence-classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_base_styleclassification_subjective_neutral_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_base_styleclassification_subjective_neutral_en.md new file mode 100644 index 00000000000000..dd1a16367eca07 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_base_styleclassification_subjective_neutral_en.md @@ -0,0 +1,111 @@ +--- +layout: model +title: English BertForSequenceClassification Base Cased model (from cffl) +author: John Snow Labs +name: bert_classifier_base_styleclassification_subjective_neutral +date: 2023-10-25 +tags: [bert, sequence_classification, classification, open_source, en, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-styleclassification-subjective-neutral` is a English model originally trained by `cffl`. + +## Predicted Entities + +`NEUTRAL`, `SUBJECTIVE` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_base_styleclassification_subjective_neutral_en_5.1.4_3.4_1698268337507.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_base_styleclassification_subjective_neutral_en_5.1.4_3.4_1698268337507.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_base_styleclassification_subjective_neutral","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_base_styleclassification_subjective_neutral","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded)) + +val data = Seq("PUT YOUR STRING HERE").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.base.by_cffl").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_base_styleclassification_subjective_neutral| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/cffl/bert-base-styleclassification-subjective-neutral +- https://arxiv.org/pdf/1911.09709.pdf +- https://arxiv.org/pdf/1703.01365.pdf +- https://github.com/openai/gpt-2/blob/master/model_card.md#out-of-scope-use-cases +- https://github.com/fastforwardlabs/text-style-transfer/blob/main/scripts/train/classifier/train_classifier.py +- https://github.com/fastforwardlabs/text-style-transfer/blob/main/notebooks/WNC_full_style_classifier_evaluation.ipynb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_base_uncased_debiased_nli_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_base_uncased_debiased_nli_en.md new file mode 100644 index 00000000000000..65af7d34269bd2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_base_uncased_debiased_nli_en.md @@ -0,0 +1,107 @@ +--- +layout: model +title: English BertForSequenceClassification Base Uncased model (from tomhosking) +author: John Snow Labs +name: bert_classifier_base_uncased_debiased_nli +date: 2023-10-25 +tags: [bert, sequence_classification, classification, open_source, en, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-uncased-debiased-nli` is a English model originally trained by `tomhosking`. + +## Predicted Entities + +`NEUTRAL`, `CONTRADICTION`, `ENTAILMENT` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_base_uncased_debiased_nli_en_5.1.4_3.4_1698203231872.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_base_uncased_debiased_nli_en_5.1.4_3.4_1698203231872.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_base_uncased_debiased_nli","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_base_uncased_debiased_nli","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded)) + +val data = Seq("PUT YOUR STRING HERE").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.uncased_base.by_tomhosking").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_base_uncased_debiased_nli| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.5 MB| +|Case sensitive:|false| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/tomhosking/bert-base-uncased-debiased-nli +- https://github.com/jimmycode/gen-debiased-nli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_base_uncased_qnli_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_base_uncased_qnli_en.md new file mode 100644 index 00000000000000..97cfc0ea4ffd8f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_base_uncased_qnli_en.md @@ -0,0 +1,107 @@ +--- +layout: model +title: English BertForSequenceClassification Base Uncased model (from Li) +author: John Snow Labs +name: bert_classifier_base_uncased_qnli +date: 2023-10-25 +tags: [bert, sequence_classification, classification, open_source, en, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-uncased-qnli` is a English model originally trained by `Li`. + +## Predicted Entities + +`entailment`, `not_entailment` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_base_uncased_qnli_en_5.1.4_3.4_1698220628861.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_base_uncased_qnli_en_5.1.4_3.4_1698220628861.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_base_uncased_qnli","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_base_uncased_qnli","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded)) + +val data = Seq("PUT YOUR STRING HERE").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.uncased_base.by_li").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_base_uncased_qnli| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| +|Case sensitive:|false| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/Li/bert-base-uncased-qnli +- https://paperswithcode.com/dataset/qnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_based_uncased_sst2_e1_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_based_uncased_sst2_e1_en.md new file mode 100644 index 00000000000000..914bdc72910798 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_based_uncased_sst2_e1_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English BertForSequenceClassification Uncased model (from EhsanAghazadeh) +author: John Snow Labs +name: bert_classifier_based_uncased_sst2_e1 +date: 2023-10-25 +tags: [bert, sequence_classification, classification, open_source, en, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-based-uncased-sst2-e1` is a English model originally trained by `EhsanAghazadeh`. + +## Predicted Entities + +`negative`, `positive` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_based_uncased_sst2_e1_en_5.1.4_3.4_1698202548911.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_based_uncased_sst2_e1_en_5.1.4_3.4_1698202548911.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_based_uncased_sst2_e1","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_based_uncased_sst2_e1","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded)) + +val data = Seq("PUT YOUR STRING HERE").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.uncased_base.by_ehsanaghazadeh").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_based_uncased_sst2_e1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| +|Case sensitive:|false| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/EhsanAghazadeh/bert-based-uncased-sst2-e1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_bert_base_german_cased_gnad10_de.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_bert_base_german_cased_gnad10_de.md new file mode 100644 index 00000000000000..85d5d53ee2be45 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_bert_base_german_cased_gnad10_de.md @@ -0,0 +1,106 @@ +--- +layout: model +title: German BertForSequenceClassification Base Cased model (from Mathking) +author: John Snow Labs +name: bert_classifier_bert_base_german_cased_gnad10 +date: 2023-10-25 +tags: [de, open_source, bert, sequence_classification, classification, onnx] +task: Text Classification +language: de +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-german-cased-gnad10` is a German model originally trained by `Mathking`. + +## Predicted Entities + +`Wirtschaft`, `Panorama`, `Web`, `Inland`, `Etat`, `Wissenschaft`, `International`, `Sport`, `Kultur` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_bert_base_german_cased_gnad10_de_5.1.4_3.4_1698224767090.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_bert_base_german_cased_gnad10_de_5.1.4_3.4_1698224767090.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_bert_base_german_cased_gnad10","de") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_bert_base_german_cased_gnad10","de") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("de.classify.bert.cased_base.by_mathking").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_bert_base_german_cased_gnad10| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|de| +|Size:|409.1 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/Mathking/bert-base-german-cased-gnad10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_bert_base_uncased_hatexplain_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_bert_base_uncased_hatexplain_en.md new file mode 100644 index 00000000000000..98ae5dfe4d8504 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_bert_base_uncased_hatexplain_en.md @@ -0,0 +1,107 @@ +--- +layout: model +title: English BertForSequenceClassification Base Uncased model (from Hate-speech-CNERG) +author: John Snow Labs +name: bert_classifier_bert_base_uncased_hatexplain +date: 2023-10-25 +tags: [en, open_source, bert, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-uncased-hatexplain` is a English model originally trained by `Hate-speech-CNERG`. + +## Predicted Entities + +`offensive`, `hate speech`, `normal` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_bert_base_uncased_hatexplain_en_5.1.4_3.4_1698205549652.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_bert_base_uncased_hatexplain_en_5.1.4_3.4_1698205549652.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_bert_base_uncased_hatexplain","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_bert_base_uncased_hatexplain","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.hate.uncased_base").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_bert_base_uncased_hatexplain| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| +|Case sensitive:|false| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/Hate-speech-CNERG/bert-base-uncased-hatexplain +- https://github.com/punyajoy/HateXplain \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_bert_base_uncased_hatexplain_rationale_two_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_bert_base_uncased_hatexplain_rationale_two_en.md new file mode 100644 index 00000000000000..a9fb07ba3ab14f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_bert_base_uncased_hatexplain_rationale_two_en.md @@ -0,0 +1,112 @@ +--- +layout: model +title: English BertForSequenceClassification Base Uncased model (from Hate-speech-CNERG) +author: John Snow Labs +name: bert_classifier_bert_base_uncased_hatexplain_rationale_two +date: 2023-10-25 +tags: [en, open_source, bert, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-uncased-hatexplain-rationale-two` is a English model originally trained by `Hate-speech-CNERG`. + +## Predicted Entities + +`NORMAL`, `ABUSIVE` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_bert_base_uncased_hatexplain_rationale_two_en_5.1.4_3.4_1698205286125.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_bert_base_uncased_hatexplain_rationale_two_en_5.1.4_3.4_1698205286125.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_bert_base_uncased_hatexplain_rationale_two","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_bert_base_uncased_hatexplain_rationale_two","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.hate.uncased_base.by_hate_speech_cnerg").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_bert_base_uncased_hatexplain_rationale_two| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| +|Case sensitive:|false| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/Hate-speech-CNERG/bert-base-uncased-hatexplain-rationale-two +- https://arxiv.org/abs/2012.10289 +- https://github.com/punyajoy/HateXplain +- https://aclanthology.org/2021.acl-long.330.pdf +- https://dl.acm.org/doi/pdf/10.1145/3442188.3445922 +- https://github.com/hate-alert/HateXplain/tree/master/Preprocess +- https://arxiv.org/pdf/2012.10289.pdf \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_bert_finetuning_cn_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_bert_finetuning_cn_en.md new file mode 100644 index 00000000000000..c505a0574fa23e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_bert_finetuning_cn_en.md @@ -0,0 +1,107 @@ +--- +layout: model +title: English BertForSequenceClassification Cased model (from LiYouYou) +author: John Snow Labs +name: bert_classifier_bert_finetuning_cn +date: 2023-10-25 +tags: [en, open_source, bert, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert_finetuning_cn` is a English model originally trained by `LiYouYou`. + +## Predicted Entities + +`positive`, `negative` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_bert_finetuning_cn_en_5.1.4_3.4_1698200944254.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_bert_finetuning_cn_en_5.1.4_3.4_1698200944254.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_bert_finetuning_cn","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_bert_finetuning_cn","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.glue.finetuning_").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_bert_finetuning_cn| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/LiYouYou/bert_finetuning_cn +- https://paperswithcode.com/sota?task=Text+Classification&dataset=GLUE+SST2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_bert_large_hatexplain_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_bert_large_hatexplain_en.md new file mode 100644 index 00000000000000..e8283953cbdeb7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_bert_large_hatexplain_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English BertForSequenceClassification Large Cased model (from TehranNLP-org) +author: John Snow Labs +name: bert_classifier_bert_large_hatexplain +date: 2023-10-25 +tags: [en, open_source, bert, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-large-hateXplain` is a English model originally trained by `TehranNLP-org`. + +## Predicted Entities + +`offensive`, `normal`, `hatespeech` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_bert_large_hatexplain_en_5.1.4_3.4_1698195127535.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_bert_large_hatexplain_en_5.1.4_3.4_1698195127535.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_bert_large_hatexplain","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_bert_large_hatexplain","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.hate.large").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_bert_large_hatexplain| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/TehranNLP-org/bert-large-hateXplain \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_biobert_v1.1_pub_section_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_biobert_v1.1_pub_section_en.md new file mode 100644 index 00000000000000..94ca584f5f89e2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_biobert_v1.1_pub_section_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English BertForSequenceClassification Cased model (from ml4pubmed) +author: John Snow Labs +name: bert_classifier_biobert_v1.1_pub_section +date: 2023-10-25 +tags: [en, open_source, bert, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `biobert-v1.1_pub_section` is a English model originally trained by `ml4pubmed`. + +## Predicted Entities + +`METHODS`, `RESULTS`, `BACKGROUND`, `CONCLUSIONS`, `OBJECTIVE` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_biobert_v1.1_pub_section_en_5.1.4_3.4_1698200074518.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_biobert_v1.1_pub_section_en_5.1.4_3.4_1698200074518.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_biobert_v1.1_pub_section","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_biobert_v1.1_pub_section","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.biobert").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_biobert_v1.1_pub_section| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.3 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/ml4pubmed/biobert-v1.1_pub_section \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_bluebert_pubmed_uncased_l_12_h_768_a_12_pub_section_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_bluebert_pubmed_uncased_l_12_h_768_a_12_pub_section_en.md new file mode 100644 index 00000000000000..b0a0c7e9c94d39 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_bluebert_pubmed_uncased_l_12_h_768_a_12_pub_section_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English BertForSequenceClassification Uncased model (from ml4pubmed) +author: John Snow Labs +name: bert_classifier_bluebert_pubmed_uncased_l_12_h_768_a_12_pub_section +date: 2023-10-25 +tags: [en, open_source, bert, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bluebert-pubmed-uncased-L-12-H-768-A-12_pub_section` is a English model originally trained by `ml4pubmed`. + +## Predicted Entities + +`METHODS`, `RESULTS`, `BACKGROUND`, `CONCLUSIONS`, `OBJECTIVE` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_bluebert_pubmed_uncased_l_12_h_768_a_12_pub_section_en_5.1.4_3.4_1698200619835.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_bluebert_pubmed_uncased_l_12_h_768_a_12_pub_section_en_5.1.4_3.4_1698200619835.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_bluebert_pubmed_uncased_l_12_h_768_a_12_pub_section","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_bluebert_pubmed_uncased_l_12_h_768_a_12_pub_section","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.pubmed_bluebert.uncased_12l_768d_a12a_768d").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_bluebert_pubmed_uncased_l_12_h_768_a_12_pub_section| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.3 MB| +|Case sensitive:|false| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/ml4pubmed/bluebert-pubmed-uncased-L-12-H-768-A-12_pub_section \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_dehate_mono_indonesian_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_dehate_mono_indonesian_en.md new file mode 100644 index 00000000000000..3abbbab1c37120 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_dehate_mono_indonesian_en.md @@ -0,0 +1,108 @@ +--- +layout: model +title: English BertForSequenceClassification Cased model (from Hate-speech-CNERG) +author: John Snow Labs +name: bert_classifier_dehate_mono_indonesian +date: 2023-10-25 +tags: [bert, sequence_classification, classification, open_source, en, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `dehatebert-mono-indonesian` is a English model originally trained by `Hate-speech-CNERG`. + +## Predicted Entities + +`HATE`, `NON_HATE` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_dehate_mono_indonesian_en_5.1.4_3.4_1698207541153.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_dehate_mono_indonesian_en_5.1.4_3.4_1698207541153.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_dehate_mono_indonesian","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_dehate_mono_indonesian","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded)) + +val data = Seq("PUT YOUR STRING HERE").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.hate.mono_indonesian.by_hate_speech_cnerg").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_dehate_mono_indonesian| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|627.7 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/Hate-speech-CNERG/dehatebert-mono-indonesian +- https://github.com/punyajoy/DE-LIMIT +- https://arxiv.org/abs/2004.06465 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_distil_base_uncased_finetuned_emotion_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_distil_base_uncased_finetuned_emotion_en.md new file mode 100644 index 00000000000000..537fa80c9e5471 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_distil_base_uncased_finetuned_emotion_en.md @@ -0,0 +1,107 @@ +--- +layout: model +title: English BertForSequenceClassification Base Uncased model (from Tahsin) +author: John Snow Labs +name: bert_classifier_distil_base_uncased_finetuned_emotion +date: 2023-10-25 +tags: [bert, sequence_classification, classification, open_source, en, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `distilbert-base-uncased-finetuned-emotion` is a English model originally trained by `Tahsin`. + +## Predicted Entities + +`sadness`, `joy`, `love`, `anger`, `surprise`, `fear` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_distil_base_uncased_finetuned_emotion_en_5.1.4_3.4_1698249889650.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_distil_base_uncased_finetuned_emotion_en_5.1.4_3.4_1698249889650.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_distil_base_uncased_finetuned_emotion","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_distil_base_uncased_finetuned_emotion","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded)) + +val data = Seq("PUT YOUR STRING HERE").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.emotion.distilled_uncased_base_finetuned").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_distil_base_uncased_finetuned_emotion| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| +|Case sensitive:|false| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/Tahsin/distilbert-base-uncased-finetuned-emotion +- https://paperswithcode.com/sota?task=Text+Classification&dataset=emotion \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_finbert_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_finbert_en.md new file mode 100644 index 00000000000000..6cfa5cff102591 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_finbert_en.md @@ -0,0 +1,109 @@ +--- +layout: model +title: English BertForSequenceClassification Cased model (from ProsusAI) +author: John Snow Labs +name: bert_classifier_finbert +date: 2023-10-25 +tags: [en, open_source, bert, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `finbert` is a English model originally trained by `ProsusAI`. + +## Predicted Entities + +`neutral`, `positive`, `negative` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_finbert_en_5.1.4_3.4_1698233630506.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_finbert_en_5.1.4_3.4_1698233630506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_finbert","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_finbert","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.by_prosusai").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_finbert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/ProsusAI/finbert +- https://www.researchgate.net/publication/251231107_Good_Debt_or_Bad_Debt_Detecting_Semantic_Orientations_in_Economic_Texts +- https://arxiv.org/abs/1908.10063 +- https://medium.com/prosus-ai-tech-blog/finbert-financial-sentiment-analysis-with-bert-b277a3607101 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_finbert_esg_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_finbert_esg_en.md new file mode 100644 index 00000000000000..c7bfb278e41602 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_finbert_esg_en.md @@ -0,0 +1,107 @@ +--- +layout: model +title: English BertForSequenceClassification Cased model (from yiyanghkust) +author: John Snow Labs +name: bert_classifier_finbert_esg +date: 2023-10-25 +tags: [en, open_source, bert, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `finbert-esg` is a English model originally trained by `yiyanghkust`. + +## Predicted Entities + +`None`, `Governance`, `Environmental`, `Social` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_finbert_esg_en_5.1.4_3.4_1698246278299.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_finbert_esg_en_5.1.4_3.4_1698246278299.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_finbert_esg","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_finbert_esg","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.esg.bert.by_yiyanghkust").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_finbert_esg| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.6 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/yiyanghkust/finbert-esg +- https://finbert.ai/ \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_german_sentiment_twitter_de.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_german_sentiment_twitter_de.md new file mode 100644 index 00000000000000..b9e3057f329e89 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_german_sentiment_twitter_de.md @@ -0,0 +1,106 @@ +--- +layout: model +title: German BertForSequenceClassification Cased model (from JP040) +author: John Snow Labs +name: bert_classifier_german_sentiment_twitter +date: 2023-10-25 +tags: [bert, sequence_classification, classification, open_source, de, onnx] +task: Text Classification +language: de +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-german-sentiment-twitter` is a German model originally trained by `JP040`. + +## Predicted Entities + +`positive`, `negative`, `neutral` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_german_sentiment_twitter_de_5.1.4_3.4_1698212459845.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_german_sentiment_twitter_de_5.1.4_3.4_1698212459845.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_german_sentiment_twitter","de") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded]) + +data = spark.createDataFrame([["Ich liebe Spark NLP"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_german_sentiment_twitter","de") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded)) + +val data = Seq("Ich liebe Spark NLP").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("de.classify.bert.sentiment_twitter.").predict("""Ich liebe Spark NLP""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_german_sentiment_twitter| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|de| +|Size:|408.1 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/JP040/bert-german-sentiment-twitter \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_hashtag_tonga_tonga_islands_hashtag_20_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_hashtag_tonga_tonga_islands_hashtag_20_en.md new file mode 100644 index 00000000000000..253eea800bf39d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_hashtag_tonga_tonga_islands_hashtag_20_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_classifier_hashtag_tonga_tonga_islands_hashtag_20 BertForSequenceClassification from Bryan0123 +author: John Snow Labs +name: bert_classifier_hashtag_tonga_tonga_islands_hashtag_20 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_hashtag_tonga_tonga_islands_hashtag_20` is a English model originally trained by Bryan0123. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_hashtag_tonga_tonga_islands_hashtag_20_en_5.1.4_3.4_1698250323134.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_hashtag_tonga_tonga_islands_hashtag_20_en_5.1.4_3.4_1698250323134.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_classifier_hashtag_tonga_tonga_islands_hashtag_20","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_classifier_hashtag_tonga_tonga_islands_hashtag_20","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_hashtag_tonga_tonga_islands_hashtag_20| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Bryan0123/bert-hashtag-to-hashtag-20 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_jeremiahz_base_uncased_mrpc_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_jeremiahz_base_uncased_mrpc_en.md new file mode 100644 index 00000000000000..4efa56ffda730e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_jeremiahz_base_uncased_mrpc_en.md @@ -0,0 +1,107 @@ +--- +layout: model +title: English BertForSequenceClassification Base Uncased model (from JeremiahZ) +author: John Snow Labs +name: bert_classifier_jeremiahz_base_uncased_mrpc +date: 2023-10-25 +tags: [en, open_source, bert, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-uncased-mrpc` is a English model originally trained by `JeremiahZ`. + +## Predicted Entities + +`not_equivalent`, `equivalent` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_jeremiahz_base_uncased_mrpc_en_5.1.4_3.4_1698192700235.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_jeremiahz_base_uncased_mrpc_en_5.1.4_3.4_1698192700235.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_jeremiahz_base_uncased_mrpc","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_jeremiahz_base_uncased_mrpc","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.glue.uncased_base.by_JeremiahZ").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_jeremiahz_base_uncased_mrpc| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| +|Case sensitive:|false| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/JeremiahZ/bert-base-uncased-mrpc +- https://paperswithcode.com/sota?task=Text+Classification&dataset=GLUE+MRPC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_m_corona_tweets_belgium_topics_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_m_corona_tweets_belgium_topics_en.md new file mode 100644 index 00000000000000..27de1ce5894b8f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_m_corona_tweets_belgium_topics_en.md @@ -0,0 +1,107 @@ +--- +layout: model +title: English BertForSequenceClassification Cased model (from DTAI-KULeuven) +author: John Snow Labs +name: bert_classifier_m_corona_tweets_belgium_topics +date: 2023-10-25 +tags: [bert, sequence_classification, classification, open_source, en, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `mbert-corona-tweets-belgium-topics` is a English model originally trained by `DTAI-KULeuven`. + +## Predicted Entities + +`masks`, `testing`, `lockdown`, `quarantine`, `closing-horeca`, `not-applicable`, `vaccine`, `curfew`, `other-measure`, `schools` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_m_corona_tweets_belgium_topics_en_5.1.4_3.4_1698193105422.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_m_corona_tweets_belgium_topics_en_5.1.4_3.4_1698193105422.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_m_corona_tweets_belgium_topics","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_m_corona_tweets_belgium_topics","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded)) + +val data = Seq("PUT YOUR STRING HERE").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.tweet.by_dtai_kuleuven").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_m_corona_tweets_belgium_topics| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|667.3 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/DTAI-KULeuven/mbert-corona-tweets-belgium-topics +- http://arxiv.org/abs/2104.09947 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_mbert_corona_tweets_belgium_curfew_support_xx.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_mbert_corona_tweets_belgium_curfew_support_xx.md new file mode 100644 index 00000000000000..27c1080a213b6e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_mbert_corona_tweets_belgium_curfew_support_xx.md @@ -0,0 +1,107 @@ +--- +layout: model +title: Multilingual BertForSequenceClassification Cased model (from DTAI-KULeuven) +author: John Snow Labs +name: bert_classifier_mbert_corona_tweets_belgium_curfew_support +date: 2023-10-25 +tags: [en, fr, nl, open_source, bert, sequence_classification, classification, xx, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `mbert-corona-tweets-belgium-curfew-support` is a Multilingual model originally trained by `DTAI-KULeuven`. + +## Predicted Entities + + + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_mbert_corona_tweets_belgium_curfew_support_xx_5.1.4_3.4_1698192742817.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_mbert_corona_tweets_belgium_curfew_support_xx_5.1.4_3.4_1698192742817.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_mbert_corona_tweets_belgium_curfew_support","xx") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_mbert_corona_tweets_belgium_curfew_support","xx") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("xx.classify.bert.tweet.").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_mbert_corona_tweets_belgium_curfew_support| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|667.3 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/DTAI-KULeuven/mbert-corona-tweets-belgium-curfew-support +- http://arxiv.org/abs/2104.09947 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_prot_bfd_localization_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_prot_bfd_localization_en.md new file mode 100644 index 00000000000000..636458196bfb2d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_prot_bfd_localization_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English BertForSequenceClassification Cased model (from Rostlab) +author: John Snow Labs +name: bert_classifier_prot_bfd_localization +date: 2023-10-25 +tags: [bert, sequence_classification, classification, open_source, en, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `prot_bert_bfd_localization` is a English model originally trained by `Rostlab`. + +## Predicted Entities + +`Mitochondrion`, `Plastid`, `Extracellular`, `Golgi.apparatus`, `Lysosome/Vacuole`, `Endoplasmic.reticulum`, `Cell.membrane`, `Cytoplasm`, `Peroxisome`, `Nucleus` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_prot_bfd_localization_en_5.1.4_3.4_1698242237342.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_prot_bfd_localization_en_5.1.4_3.4_1698242237342.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_prot_bfd_localization","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_prot_bfd_localization","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded)) + +val data = Seq("PUT YOUR STRING HERE").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.prot_bfd_localization.bert.by_rostlab").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_prot_bfd_localization| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.6 GB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/Rostlab/prot_bert_bfd_localization \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_reddit_tc_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_reddit_tc_en.md new file mode 100644 index 00000000000000..4515f12378fc52 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_reddit_tc_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English BertForSequenceClassification Cased model (from Fan-s) +author: John Snow Labs +name: bert_classifier_reddit_tc +date: 2023-10-25 +tags: [bert, sequence_classification, classification, open_source, en, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `reddit-tc-bert` is a English model originally trained by `Fan-s`. + +## Predicted Entities + +`matched`, `unmatched` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_reddit_tc_en_5.1.4_3.4_1698204461175.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_reddit_tc_en_5.1.4_3.4_1698204461175.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_reddit_tc","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_reddit_tc","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded)) + +val data = Seq("PUT YOUR STRING HERE").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.by_fan_s").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_reddit_tc| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/Fan-s/reddit-tc-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_riad_finetuned_mrpc_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_riad_finetuned_mrpc_en.md new file mode 100644 index 00000000000000..a9f8b2152d0c4c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_riad_finetuned_mrpc_en.md @@ -0,0 +1,107 @@ +--- +layout: model +title: English BertForSequenceClassification Cased model (from Riad) +author: John Snow Labs +name: bert_classifier_riad_finetuned_mrpc +date: 2023-10-25 +tags: [bert, sequence_classification, classification, open_source, en, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `finetuned-bert-mrpc` is a English model originally trained by `Riad`. + +## Predicted Entities + +`equivalent`, `not equivalent` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_riad_finetuned_mrpc_en_5.1.4_3.4_1698239870016.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_riad_finetuned_mrpc_en_5.1.4_3.4_1698239870016.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_riad_finetuned_mrpc","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_riad_finetuned_mrpc","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded)) + +val data = Seq("PUT YOUR STRING HERE").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.glue.finetuned.by_Riad").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_riad_finetuned_mrpc| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/Riad/finetuned-bert-mrpc +- https://paperswithcode.com/sota?task=Text+Classification&dataset=glue \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_rubertconv_toxic_clf_ru.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_rubertconv_toxic_clf_ru.md new file mode 100644 index 00000000000000..4d8999535ab27c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_rubertconv_toxic_clf_ru.md @@ -0,0 +1,110 @@ +--- +layout: model +title: Russian BertForSequenceClassification Cased model (from IlyaGusev) +author: John Snow Labs +name: bert_classifier_rubertconv_toxic_clf +date: 2023-10-25 +tags: [ru, open_source, bert, sequence_classification, classification, onnx] +task: Text Classification +language: ru +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `rubertconv_toxic_clf` is a Russian model originally trained by `IlyaGusev`. + +## Predicted Entities + +`toxic`, `neutral` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_rubertconv_toxic_clf_ru_5.1.4_3.4_1698210881499.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_rubertconv_toxic_clf_ru_5.1.4_3.4_1698210881499.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_rubertconv_toxic_clf","ru") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_rubertconv_toxic_clf","ru") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("ru.classify.bert").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_rubertconv_toxic_clf| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|ru| +|Size:|664.4 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/IlyaGusev/rubertconv_toxic_clf +- https://www.kaggle.com/blackmoon/russian-language-toxic-comments +- https://www.kaggle.com/alexandersemiletov/toxic-russian-comments +- https://toloka.ai/ru/datasets +- https://github.com/Koziev/NLP_Datasets/blob/master/Conversations/Data \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_russian_base_srl_ru.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_russian_base_srl_ru.md new file mode 100644 index 00000000000000..a77f5d7f698f53 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_russian_base_srl_ru.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Russian bert_classifier_russian_base_srl BertForSequenceClassification from Rexhaif +author: John Snow Labs +name: bert_classifier_russian_base_srl +date: 2023-10-25 +tags: [bert, ru, open_source, sequence_classification, onnx] +task: Text Classification +language: ru +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_russian_base_srl` is a Russian model originally trained by Rexhaif. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_russian_base_srl_ru_5.1.4_3.4_1698236889529.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_russian_base_srl_ru_5.1.4_3.4_1698236889529.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_classifier_russian_base_srl","ru")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_classifier_russian_base_srl","ru") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_russian_base_srl| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|ru| +|Size:|669.3 MB| + +## References + +https://huggingface.co/Rexhaif/rubert-base-srl \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_scibert_scivocab_cased_pub_section_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_scibert_scivocab_cased_pub_section_en.md new file mode 100644 index 00000000000000..0f005e3151c891 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_scibert_scivocab_cased_pub_section_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English BertForSequenceClassification Cased model (from ml4pubmed) +author: John Snow Labs +name: bert_classifier_scibert_scivocab_cased_pub_section +date: 2023-10-25 +tags: [en, open_source, bert, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `scibert-scivocab-cased_pub_section` is a English model originally trained by `ml4pubmed`. + +## Predicted Entities + +`CONCLUSIONS`, `METHODS`, `OBJECTIVE`, `RESULTS`, `BACKGROUND` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_scibert_scivocab_cased_pub_section_en_5.1.4_3.4_1698199767413.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_scibert_scivocab_cased_pub_section_en_5.1.4_3.4_1698199767413.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_scibert_scivocab_cased_pub_section","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_scibert_scivocab_cased_pub_section","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.scibert.scibert.cased").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_scibert_scivocab_cased_pub_section| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|412.1 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/ml4pubmed/scibert-scivocab-cased_pub_section \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_scibert_scivocab_uncased_pub_section_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_scibert_scivocab_uncased_pub_section_en.md new file mode 100644 index 00000000000000..4ee0c0e6e2724e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_scibert_scivocab_uncased_pub_section_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English BertForSequenceClassification Uncased model (from ml4pubmed) +author: John Snow Labs +name: bert_classifier_scibert_scivocab_uncased_pub_section +date: 2023-10-25 +tags: [en, open_source, bert, sequence_classification, classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `scibert-scivocab-uncased_pub_section` is a English model originally trained by `ml4pubmed`. + +## Predicted Entities + +`CONCLUSIONS`, `METHODS`, `OBJECTIVE`, `RESULTS`, `BACKGROUND` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_scibert_scivocab_uncased_pub_section_en_5.1.4_3.4_1698200342570.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_scibert_scivocab_uncased_pub_section_en_5.1.4_3.4_1698200342570.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_scibert_scivocab_uncased_pub_section","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCols(Array("text")) + .setOutputCols(Array("document")) + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val seq_classifier = BertForSequenceClassification.pretrained("bert_classifier_scibert_scivocab_uncased_pub_section","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.scibert.scibert.uncased").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_scibert_scivocab_uncased_pub_section| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|412.2 MB| +|Case sensitive:|false| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/ml4pubmed/scibert-scivocab-uncased_pub_section \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_shahma_finetuned_mrpc_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_shahma_finetuned_mrpc_en.md new file mode 100644 index 00000000000000..346eff587dc41c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_shahma_finetuned_mrpc_en.md @@ -0,0 +1,107 @@ +--- +layout: model +title: English BertForSequenceClassification Cased model (from shahma) +author: John Snow Labs +name: bert_classifier_shahma_finetuned_mrpc +date: 2023-10-25 +tags: [bert, sequence_classification, classification, open_source, en, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `finetuned-bert-mrpc` is a English model originally trained by `shahma`. + +## Predicted Entities + +`equivalent`, `not equivalent` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_shahma_finetuned_mrpc_en_5.1.4_3.4_1698262498901.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_shahma_finetuned_mrpc_en_5.1.4_3.4_1698262498901.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_shahma_finetuned_mrpc","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_shahma_finetuned_mrpc","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded)) + +val data = Seq("PUT YOUR STRING HERE").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.glue.finetuned.by_shahma").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_shahma_finetuned_mrpc| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/shahma/finetuned-bert-mrpc +- https://paperswithcode.com/sota?task=Text+Classification&dataset=glue \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_tiny_qqp_distilled_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_tiny_qqp_distilled_en.md new file mode 100644 index 00000000000000..513f8ca47ecea4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_tiny_qqp_distilled_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English BertForSequenceClassification Tiny Cased model (from Sayan01) +author: John Snow Labs +name: bert_classifier_tiny_qqp_distilled +date: 2023-10-25 +tags: [bert, sequence_classification, classification, open_source, en, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `tiny-bert-qqp-distilled` is a English model originally trained by `Sayan01`. + +## Predicted Entities + +`duplicate`, `not_duplicate` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_tiny_qqp_distilled_en_5.1.4_3.4_1698211704999.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_tiny_qqp_distilled_en_5.1.4_3.4_1698211704999.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_tiny_qqp_distilled","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_tiny_qqp_distilled","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded)) + +val data = Seq("PUT YOUR STRING HERE").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.distilled_tiny.by_sayan01").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_tiny_qqp_distilled| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|54.2 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/Sayan01/tiny-bert-qqp-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_tiny_sst2_distilled_l4_h_512_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_tiny_sst2_distilled_l4_h_512_en.md new file mode 100644 index 00000000000000..c8dc96cf1f6dfe --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_tiny_sst2_distilled_l4_h_512_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English BertForSequenceClassification Tiny Cased model (from Smith123) +author: John Snow Labs +name: bert_classifier_tiny_sst2_distilled_l4_h_512 +date: 2023-10-25 +tags: [bert, sequence_classification, classification, open_source, en, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `tiny-bert-sst2-distilled_L4_H_512` is a English model originally trained by `Smith123`. + +## Predicted Entities + +`positive`, `negative` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_tiny_sst2_distilled_l4_h_512_en_5.1.4_3.4_1698213280716.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_tiny_sst2_distilled_l4_h_512_en_5.1.4_3.4_1698213280716.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_tiny_sst2_distilled_l4_h_512","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_tiny_sst2_distilled_l4_h_512","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded)) + +val data = Seq("PUT YOUR STRING HERE").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.distilled_512d_tiny_512d").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_tiny_sst2_distilled_l4_h_512| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|107.9 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/Smith123/tiny-bert-sst2-distilled_L4_H_512 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_tiny_sst2_distilled_l6_h128_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_tiny_sst2_distilled_l6_h128_en.md new file mode 100644 index 00000000000000..f06036a5eb1572 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_classifier_tiny_sst2_distilled_l6_h128_en.md @@ -0,0 +1,106 @@ +--- +layout: model +title: English BertForSequenceClassification Tiny Cased model (from Smith123) +author: John Snow Labs +name: bert_classifier_tiny_sst2_distilled_l6_h128 +date: 2023-10-25 +tags: [bert, sequence_classification, classification, open_source, en, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `tiny-bert-sst2-distilled_L6_H128` is a English model originally trained by `Smith123`. + +## Predicted Entities + +`positive`, `negative` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_tiny_sst2_distilled_l6_h128_en_5.1.4_3.4_1698213100526.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_tiny_sst2_distilled_l6_h128_en_5.1.4_3.4_1698213100526.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_tiny_sst2_distilled_l6_h128","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer,sequenceClassifier_loaded]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols(Array("document")) + .setOutputCol("token") + +val sequenceClassifier_loaded = BertForSequenceClassification.pretrained("bert_classifier_tiny_sst2_distilled_l6_h128","en") + .setInputCols(Array("document", "token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer,sequenceClassifier_loaded)) + +val data = Seq("PUT YOUR STRING HERE").toDF("text") + +val result = pipeline.fit(data).transform(data) +``` + +{:.nlu-block} +```python +import nlu +nlu.load("en.classify.bert.distilled_tiny.by_smith123").predict("""PUT YOUR STRING HERE""") +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_tiny_sst2_distilled_l6_h128| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|19.7 MB| +|Case sensitive:|true| +|Max sentence length:|256| + +## References + +References + +- https://huggingface.co/Smith123/tiny-bert-sst2-distilled_L6_H128 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_cn_finetuning_connor_tech_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_cn_finetuning_connor_tech_en.md new file mode 100644 index 00000000000000..447a0864e1b108 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_cn_finetuning_connor_tech_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_cn_finetuning_connor_tech BertForSequenceClassification from Connor-tech +author: John Snow Labs +name: bert_cn_finetuning_connor_tech +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_cn_finetuning_connor_tech` is a English model originally trained by Connor-tech. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_cn_finetuning_connor_tech_en_5.1.4_3.4_1698192414295.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_cn_finetuning_connor_tech_en_5.1.4_3.4_1698192414295.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_cn_finetuning_connor_tech","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_cn_finetuning_connor_tech","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_cn_finetuning_connor_tech| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/Connor-tech/bert_cn_finetuning \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_cn_finetuning_itcastai_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_cn_finetuning_itcastai_en.md new file mode 100644 index 00000000000000..987d63659303c7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_cn_finetuning_itcastai_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_cn_finetuning_itcastai BertForSequenceClassification from ItcastAI +author: John Snow Labs +name: bert_cn_finetuning_itcastai +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_cn_finetuning_itcastai` is a English model originally trained by ItcastAI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_cn_finetuning_itcastai_en_5.1.4_3.4_1698211264091.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_cn_finetuning_itcastai_en_5.1.4_3.4_1698211264091.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_cn_finetuning_itcastai","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_cn_finetuning_itcastai","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_cn_finetuning_itcastai| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/ItcastAI/bert_cn_finetuning \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_cn_finetunning_itcastai_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_cn_finetunning_itcastai_en.md new file mode 100644 index 00000000000000..34df6ea0027f95 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_cn_finetunning_itcastai_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_cn_finetunning_itcastai BertForSequenceClassification from ItcastAI +author: John Snow Labs +name: bert_cn_finetunning_itcastai +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_cn_finetunning_itcastai` is a English model originally trained by ItcastAI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_cn_finetunning_itcastai_en_5.1.4_3.4_1698211451875.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_cn_finetunning_itcastai_en_5.1.4_3.4_1698211451875.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_cn_finetunning_itcastai","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_cn_finetunning_itcastai","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_cn_finetunning_itcastai| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/ItcastAI/bert_cn_finetunning \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_cn_finetunning_jovenpai_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_cn_finetunning_jovenpai_en.md new file mode 100644 index 00000000000000..05260f273ec9ed --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_cn_finetunning_jovenpai_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_cn_finetunning_jovenpai BertForSequenceClassification from JovenPai +author: John Snow Labs +name: bert_cn_finetunning_jovenpai +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_cn_finetunning_jovenpai` is a English model originally trained by JovenPai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_cn_finetunning_jovenpai_en_5.1.4_3.4_1698219841571.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_cn_finetunning_jovenpai_en_5.1.4_3.4_1698219841571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_cn_finetunning_jovenpai","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_cn_finetunning_jovenpai","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_cn_finetunning_jovenpai| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.3 MB| + +## References + +https://huggingface.co/JovenPai/bert_cn_finetunning \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_cnn_news_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_cnn_news_en.md new file mode 100644 index 00000000000000..8c7b8108a52125 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_cnn_news_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_cnn_news BertForSequenceClassification from AyoubChLin +author: John Snow Labs +name: bert_cnn_news +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_cnn_news` is a English model originally trained by AyoubChLin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_cnn_news_en_5.1.4_3.4_1698245908185.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_cnn_news_en_5.1.4_3.4_1698245908185.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_cnn_news","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_cnn_news","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_cnn_news| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/AyoubChLin/bert_cnn_news \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_cola_finetuned_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_cola_finetuned_en.md new file mode 100644 index 00000000000000..0082653e8af2c5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_cola_finetuned_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_cola_finetuned BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_cola_finetuned +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_cola_finetuned` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_cola_finetuned_en_5.1.4_3.4_1698201158703.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_cola_finetuned_en_5.1.4_3.4_1698201158703.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_cola_finetuned","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_cola_finetuned","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_cola_finetuned| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-cola-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_covid_hate_finetuned_test_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_covid_hate_finetuned_test_en.md new file mode 100644 index 00000000000000..a44b81805bd508 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_covid_hate_finetuned_test_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_covid_hate_finetuned_test BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_covid_hate_finetuned_test +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_covid_hate_finetuned_test` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_covid_hate_finetuned_test_en_5.1.4_3.4_1698194103840.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_covid_hate_finetuned_test_en_5.1.4_3.4_1698194103840.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_covid_hate_finetuned_test","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_covid_hate_finetuned_test","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_covid_hate_finetuned_test| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-COVID-HATE-finetuned-test \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_deepfake_bulgarian_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_deepfake_bulgarian_en.md new file mode 100644 index 00000000000000..91a534f78f21ac --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_deepfake_bulgarian_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_deepfake_bulgarian BertForSequenceClassification from usmiva +author: John Snow Labs +name: bert_deepfake_bulgarian +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_deepfake_bulgarian` is a English model originally trained by usmiva. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_deepfake_bulgarian_en_5.1.4_3.4_1698201953411.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_deepfake_bulgarian_en_5.1.4_3.4_1698201953411.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_deepfake_bulgarian","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_deepfake_bulgarian","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_deepfake_bulgarian| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.1 MB| + +## References + +https://huggingface.co/usmiva/bert-deepfake-bg \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_deepfake_bulgarian_multiclass_bg.md b/docs/_posts/ahmedlone127/2023-10-25-bert_deepfake_bulgarian_multiclass_bg.md new file mode 100644 index 00000000000000..e73f8e0fd9bfe6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_deepfake_bulgarian_multiclass_bg.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Bulgarian bert_deepfake_bulgarian_multiclass BertForSequenceClassification from usmiva +author: John Snow Labs +name: bert_deepfake_bulgarian_multiclass +date: 2023-10-25 +tags: [bert, bg, open_source, sequence_classification, onnx] +task: Text Classification +language: bg +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_deepfake_bulgarian_multiclass` is a Bulgarian model originally trained by usmiva. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_deepfake_bulgarian_multiclass_bg_5.1.4_3.4_1698212606456.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_deepfake_bulgarian_multiclass_bg_5.1.4_3.4_1698212606456.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_deepfake_bulgarian_multiclass","bg")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_deepfake_bulgarian_multiclass","bg") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_deepfake_bulgarian_multiclass| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|bg| +|Size:|409.1 MB| + +## References + +https://huggingface.co/usmiva/bert-deepfake-bg-multiclass \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_desinform_bulgarian_bg.md b/docs/_posts/ahmedlone127/2023-10-25-bert_desinform_bulgarian_bg.md new file mode 100644 index 00000000000000..2eae055483ecdf --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_desinform_bulgarian_bg.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Bulgarian bert_desinform_bulgarian BertForSequenceClassification from usmiva +author: John Snow Labs +name: bert_desinform_bulgarian +date: 2023-10-25 +tags: [bert, bg, open_source, sequence_classification, onnx] +task: Text Classification +language: bg +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_desinform_bulgarian` is a Bulgarian model originally trained by usmiva. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_desinform_bulgarian_bg_5.1.4_3.4_1698201765003.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_desinform_bulgarian_bg_5.1.4_3.4_1698201765003.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_desinform_bulgarian","bg")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_desinform_bulgarian","bg") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_desinform_bulgarian| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|bg| +|Size:|409.1 MB| + +## References + +https://huggingface.co/usmiva/bert-desinform-bg \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_fakenews_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_fakenews_en.md new file mode 100644 index 00000000000000..12621cd2dc0b79 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_fakenews_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_fakenews BertForSequenceClassification from JKKANG +author: John Snow Labs +name: bert_fakenews +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_fakenews` is a English model originally trained by JKKANG. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fakenews_en_5.1.4_3.4_1698221382925.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fakenews_en_5.1.4_3.4_1698221382925.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_fakenews","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_fakenews","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_fakenews| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.6 MB| + +## References + +https://huggingface.co/JKKANG/bert-fakenews \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_fine_trained_w_imdb_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_fine_trained_w_imdb_en.md new file mode 100644 index 00000000000000..f16bc5633c9bdd --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_fine_trained_w_imdb_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_fine_trained_w_imdb BertForSequenceClassification from Ycuu +author: John Snow Labs +name: bert_fine_trained_w_imdb +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_fine_trained_w_imdb` is a English model originally trained by Ycuu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fine_trained_w_imdb_en_5.1.4_3.4_1698204733003.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fine_trained_w_imdb_en_5.1.4_3.4_1698204733003.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_fine_trained_w_imdb","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_fine_trained_w_imdb","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_fine_trained_w_imdb| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Ycuu/bert_fine_trained_w_imdb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_cola_huong_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_cola_huong_en.md new file mode 100644 index 00000000000000..e6c6c4486e4542 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_cola_huong_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_fine_tuned_cola_huong BertForSequenceClassification from Thi-Thu-Huong +author: John Snow Labs +name: bert_fine_tuned_cola_huong +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_fine_tuned_cola_huong` is a English model originally trained by Thi-Thu-Huong. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_cola_huong_en_5.1.4_3.4_1698215254963.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_cola_huong_en_5.1.4_3.4_1698215254963.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_fine_tuned_cola_huong","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_fine_tuned_cola_huong","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_fine_tuned_cola_huong| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Thi-Thu-Huong/bert-fine-tuned-cola-huong \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_cola_kaori1707_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_cola_kaori1707_en.md new file mode 100644 index 00000000000000..2c19c631dedd1f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_cola_kaori1707_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_fine_tuned_cola_kaori1707 BertForSequenceClassification from Kaori1707 +author: John Snow Labs +name: bert_fine_tuned_cola_kaori1707 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_fine_tuned_cola_kaori1707` is a English model originally trained by Kaori1707. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_cola_kaori1707_en_5.1.4_3.4_1698218279367.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_cola_kaori1707_en_5.1.4_3.4_1698218279367.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_fine_tuned_cola_kaori1707","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_fine_tuned_cola_kaori1707","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_fine_tuned_cola_kaori1707| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Kaori1707/bert-fine-tuned-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_cola_ramuvannela_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_cola_ramuvannela_en.md new file mode 100644 index 00000000000000..4404fa1e49869d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_cola_ramuvannela_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_fine_tuned_cola_ramuvannela BertForSequenceClassification from Ramuvannela +author: John Snow Labs +name: bert_fine_tuned_cola_ramuvannela +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_fine_tuned_cola_ramuvannela` is a English model originally trained by Ramuvannela. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_cola_ramuvannela_en_5.1.4_3.4_1698195337388.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_cola_ramuvannela_en_5.1.4_3.4_1698195337388.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_fine_tuned_cola_ramuvannela","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_fine_tuned_cola_ramuvannela","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_fine_tuned_cola_ramuvannela| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Ramuvannela/bert-fine-tuned-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_cola_sanjay1234_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_cola_sanjay1234_en.md new file mode 100644 index 00000000000000..c5d0d4852ea038 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_cola_sanjay1234_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_fine_tuned_cola_sanjay1234 BertForSequenceClassification from Sanjay1234 +author: John Snow Labs +name: bert_fine_tuned_cola_sanjay1234 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_fine_tuned_cola_sanjay1234` is a English model originally trained by Sanjay1234. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_cola_sanjay1234_en_5.1.4_3.4_1698210711894.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_cola_sanjay1234_en_5.1.4_3.4_1698210711894.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_fine_tuned_cola_sanjay1234","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_fine_tuned_cola_sanjay1234","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_fine_tuned_cola_sanjay1234| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Sanjay1234/bert-fine-tuned-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_cola_tamiti1610001_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_cola_tamiti1610001_en.md new file mode 100644 index 00000000000000..699120b642ef62 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_cola_tamiti1610001_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_fine_tuned_cola_tamiti1610001 BertForSequenceClassification from tamiti1610001 +author: John Snow Labs +name: bert_fine_tuned_cola_tamiti1610001 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_fine_tuned_cola_tamiti1610001` is a English model originally trained by tamiti1610001. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_cola_tamiti1610001_en_5.1.4_3.4_1698210205200.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_cola_tamiti1610001_en_5.1.4_3.4_1698210205200.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_fine_tuned_cola_tamiti1610001","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_fine_tuned_cola_tamiti1610001","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_fine_tuned_cola_tamiti1610001| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/tamiti1610001/bert-fine-tuned-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_english_news_2_lbl_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_english_news_2_lbl_en.md new file mode 100644 index 00000000000000..dec7f53d7ade7b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_english_news_2_lbl_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_fine_tuned_english_news_2_lbl BertForSequenceClassification from Ycuu +author: John Snow Labs +name: bert_fine_tuned_english_news_2_lbl +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_fine_tuned_english_news_2_lbl` is a English model originally trained by Ycuu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_english_news_2_lbl_en_5.1.4_3.4_1698214452492.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_english_news_2_lbl_en_5.1.4_3.4_1698214452492.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_fine_tuned_english_news_2_lbl","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_fine_tuned_english_news_2_lbl","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_fine_tuned_english_news_2_lbl| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Ycuu/bert_fine_tuned_en_news_2_lbl \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_english_news_3_lbl_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_english_news_3_lbl_en.md new file mode 100644 index 00000000000000..4a295c13f62833 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_english_news_3_lbl_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_fine_tuned_english_news_3_lbl BertForSequenceClassification from Ycuu +author: John Snow Labs +name: bert_fine_tuned_english_news_3_lbl +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_fine_tuned_english_news_3_lbl` is a English model originally trained by Ycuu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_english_news_3_lbl_en_5.1.4_3.4_1698214268656.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_english_news_3_lbl_en_5.1.4_3.4_1698214268656.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_fine_tuned_english_news_3_lbl","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_fine_tuned_english_news_3_lbl","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_fine_tuned_english_news_3_lbl| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Ycuu/bert_fine_tuned_en_news_3_lbl \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_intent_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_intent_en.md new file mode 100644 index 00000000000000..5cbea6f7d5c380 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_intent_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_fine_tuned_intent BertForSequenceClassification from deprem-ml +author: John Snow Labs +name: bert_fine_tuned_intent +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_fine_tuned_intent` is a English model originally trained by deprem-ml. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_intent_en_5.1.4_3.4_1698200105021.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_intent_en_5.1.4_3.4_1698200105021.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_fine_tuned_intent","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_fine_tuned_intent","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_fine_tuned_intent| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.5 MB| + +## References + +https://huggingface.co/deprem-ml/bert-fine-tuned-intent \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_patents_spanish_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_patents_spanish_en.md new file mode 100644 index 00000000000000..bdee19d58ee426 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_fine_tuned_patents_spanish_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_fine_tuned_patents_spanish BertForSequenceClassification from valcharriera +author: John Snow Labs +name: bert_fine_tuned_patents_spanish +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_fine_tuned_patents_spanish` is a English model originally trained by valcharriera. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_patents_spanish_en_5.1.4_3.4_1698195794094.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fine_tuned_patents_spanish_en_5.1.4_3.4_1698195794094.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_fine_tuned_patents_spanish","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_fine_tuned_patents_spanish","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_fine_tuned_patents_spanish| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.9 MB| + +## References + +https://huggingface.co/valcharriera/bert-fine-tuned-patents-spanish \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_agnews_teacher_model_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_agnews_teacher_model_en.md new file mode 100644 index 00000000000000..f13ee944ab68af --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_agnews_teacher_model_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_finetuned_agnews_teacher_model BertForSequenceClassification from tamhuynh27 +author: John Snow Labs +name: bert_finetuned_agnews_teacher_model +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_agnews_teacher_model` is a English model originally trained by tamhuynh27. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_agnews_teacher_model_en_5.1.4_3.4_1698203547452.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_agnews_teacher_model_en_5.1.4_3.4_1698203547452.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_agnews_teacher_model","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_agnews_teacher_model","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_agnews_teacher_model| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/tamhuynh27/bert-finetuned-agnews-teacher-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_banking77test_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_banking77test_en.md new file mode 100644 index 00000000000000..13924f3c328d03 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_banking77test_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_finetuned_banking77test BertForSequenceClassification from Anna-UoC +author: John Snow Labs +name: bert_finetuned_banking77test +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_banking77test` is a English model originally trained by Anna-UoC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_banking77test_en_5.1.4_3.4_1698209129829.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_banking77test_en_5.1.4_3.4_1698209129829.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_banking77test","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_banking77test","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_banking77test| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/Anna-UoC/bert_finetuned_banking77test \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_char_classification_e15_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_char_classification_e15_en.md new file mode 100644 index 00000000000000..f8ba95b835b3f2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_char_classification_e15_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_finetuned_char_classification_e15 BertForSequenceClassification from bhagasra-saurav +author: John Snow Labs +name: bert_finetuned_char_classification_e15 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_char_classification_e15` is a English model originally trained by bhagasra-saurav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_char_classification_e15_en_5.1.4_3.4_1698277567602.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_char_classification_e15_en_5.1.4_3.4_1698277567602.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_char_classification_e15","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_char_classification_e15","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_char_classification_e15| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/bhagasra-saurav/bert-finetuned-char-classification-e15 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_char_classification_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_char_classification_en.md new file mode 100644 index 00000000000000..9de3f7adae0e32 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_char_classification_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_finetuned_char_classification BertForSequenceClassification from bhagasra-saurav +author: John Snow Labs +name: bert_finetuned_char_classification +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_char_classification` is a English model originally trained by bhagasra-saurav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_char_classification_en_5.1.4_3.4_1698267584576.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_char_classification_en_5.1.4_3.4_1698267584576.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_char_classification","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_char_classification","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_char_classification| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/bhagasra-saurav/bert-finetuned-char-classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_emotion_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_emotion_en.md new file mode 100644 index 00000000000000..be5e390dba1750 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_emotion_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_finetuned_emotion BertForSequenceClassification from PascalY +author: John Snow Labs +name: bert_finetuned_emotion +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_emotion` is a English model originally trained by PascalY. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_emotion_en_5.1.4_3.4_1698201395298.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_emotion_en_5.1.4_3.4_1698201395298.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_emotion","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_emotion","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_emotion| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/PascalY/bert-finetuned-emotion \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_imdb_wakaka_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_imdb_wakaka_en.md new file mode 100644 index 00000000000000..d547e9beaecf5e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_imdb_wakaka_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_finetuned_imdb_wakaka BertForSequenceClassification from Wakaka +author: John Snow Labs +name: bert_finetuned_imdb_wakaka +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_imdb_wakaka` is a English model originally trained by Wakaka. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_imdb_wakaka_en_5.1.4_3.4_1698202367748.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_imdb_wakaka_en_5.1.4_3.4_1698202367748.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_imdb_wakaka","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_imdb_wakaka","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_imdb_wakaka| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Wakaka/bert-finetuned-imdb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_mrpc_dineshmane_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_mrpc_dineshmane_en.md new file mode 100644 index 00000000000000..049516fb106f05 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_mrpc_dineshmane_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_finetuned_mrpc_dineshmane BertForSequenceClassification from dineshmane +author: John Snow Labs +name: bert_finetuned_mrpc_dineshmane +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_mrpc_dineshmane` is a English model originally trained by dineshmane. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_mrpc_dineshmane_en_5.1.4_3.4_1698197868461.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_mrpc_dineshmane_en_5.1.4_3.4_1698197868461.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_mrpc_dineshmane","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_mrpc_dineshmane","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_mrpc_dineshmane| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/dineshmane/bert-finetuned-mrpc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_mrpc_tiansiyuan_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_mrpc_tiansiyuan_en.md new file mode 100644 index 00000000000000..2fd92f028df865 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_mrpc_tiansiyuan_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_finetuned_mrpc_tiansiyuan BertForSequenceClassification from tiansiyuan +author: John Snow Labs +name: bert_finetuned_mrpc_tiansiyuan +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_mrpc_tiansiyuan` is a English model originally trained by tiansiyuan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_mrpc_tiansiyuan_en_5.1.4_3.4_1698223815854.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_mrpc_tiansiyuan_en_5.1.4_3.4_1698223815854.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_mrpc_tiansiyuan","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_mrpc_tiansiyuan","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_mrpc_tiansiyuan| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/tiansiyuan/bert-finetuned-mrpc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_mrpc_trainerclass_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_mrpc_trainerclass_en.md new file mode 100644 index 00000000000000..a8b274e1666e24 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_mrpc_trainerclass_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_finetuned_mrpc_trainerclass BertForSequenceClassification from sara98 +author: John Snow Labs +name: bert_finetuned_mrpc_trainerclass +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_mrpc_trainerclass` is a English model originally trained by sara98. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_mrpc_trainerclass_en_5.1.4_3.4_1698265407693.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_mrpc_trainerclass_en_5.1.4_3.4_1698265407693.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_mrpc_trainerclass","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_mrpc_trainerclass","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_mrpc_trainerclass| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/sara98/bert-finetuned-mrpc-trainerclass \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_mrpc_yanael_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_mrpc_yanael_en.md new file mode 100644 index 00000000000000..da6a081a129f83 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_mrpc_yanael_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_finetuned_mrpc_yanael BertForSequenceClassification from Yanael +author: John Snow Labs +name: bert_finetuned_mrpc_yanael +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_mrpc_yanael` is a English model originally trained by Yanael. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_mrpc_yanael_en_5.1.4_3.4_1698197288978.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_mrpc_yanael_en_5.1.4_3.4_1698197288978.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_mrpc_yanael","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_mrpc_yanael","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_mrpc_yanael| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Yanael/bert-finetuned-mrpc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_slavic_languages_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_slavic_languages_en.md new file mode 100644 index 00000000000000..0d5b4740c932de --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_slavic_languages_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_finetuned_slavic_languages BertForSequenceClassification from marmolpen3 +author: John Snow Labs +name: bert_finetuned_slavic_languages +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_slavic_languages` is a English model originally trained by marmolpen3. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_slavic_languages_en_5.1.4_3.4_1698195514666.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_slavic_languages_en_5.1.4_3.4_1698195514666.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_slavic_languages","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_slavic_languages","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_slavic_languages| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/marmolpen3/bert-finetuned-sla \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_winogrande83e_058_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_winogrande83e_058_en.md new file mode 100644 index 00000000000000..8fed34946f3565 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_winogrande83e_058_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_finetuned_winogrande83e_058 BertForSequenceClassification from Kalslice +author: John Snow Labs +name: bert_finetuned_winogrande83e_058 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_winogrande83e_058` is a English model originally trained by Kalslice. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_winogrande83e_058_en_5.1.4_3.4_1698248111414.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_winogrande83e_058_en_5.1.4_3.4_1698248111414.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_winogrande83e_058","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_winogrande83e_058","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_winogrande83e_058| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Kalslice/bert-finetuned-winogrande83e-058 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_winogrande_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_winogrande_en.md new file mode 100644 index 00000000000000..da788c8034df82 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuned_winogrande_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_finetuned_winogrande BertForSequenceClassification from Kalslice +author: John Snow Labs +name: bert_finetuned_winogrande +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_winogrande` is a English model originally trained by Kalslice. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_winogrande_en_5.1.4_3.4_1698230827620.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_winogrande_en_5.1.4_3.4_1698230827620.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_winogrande","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_winogrande","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_winogrande| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Kalslice/bert-finetuned-winogrande \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_finetuning_test_itcastai_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuning_test_itcastai_en.md new file mode 100644 index 00000000000000..f0e2e41f58598e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuning_test_itcastai_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_finetuning_test_itcastai BertForSequenceClassification from ItcastAI +author: John Snow Labs +name: bert_finetuning_test_itcastai +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuning_test_itcastai` is a English model originally trained by ItcastAI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuning_test_itcastai_en_5.1.4_3.4_1698211632257.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuning_test_itcastai_en_5.1.4_3.4_1698211632257.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuning_test_itcastai","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuning_test_itcastai","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuning_test_itcastai| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ItcastAI/bert_finetuning_test \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_finetuning_test_milian_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuning_test_milian_en.md new file mode 100644 index 00000000000000..8b245b1435a894 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_finetuning_test_milian_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_finetuning_test_milian BertForSequenceClassification from Milian +author: John Snow Labs +name: bert_finetuning_test_milian +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuning_test_milian` is a English model originally trained by Milian. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuning_test_milian_en_5.1.4_3.4_1698225530685.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuning_test_milian_en_5.1.4_3.4_1698225530685.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuning_test_milian","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuning_test_milian","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuning_test_milian| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Milian/bert_finetuning_test \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_finetunning_test_itcastai_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_finetunning_test_itcastai_en.md new file mode 100644 index 00000000000000..9340812df09e45 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_finetunning_test_itcastai_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_finetunning_test_itcastai BertForSequenceClassification from ItcastAI +author: John Snow Labs +name: bert_finetunning_test_itcastai +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetunning_test_itcastai` is a English model originally trained by ItcastAI. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetunning_test_itcastai_en_5.1.4_3.4_1698211833653.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetunning_test_itcastai_en_5.1.4_3.4_1698211833653.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetunning_test_itcastai","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetunning_test_itcastai","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetunning_test_itcastai| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ItcastAI/bert_finetunning_test \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_finetunning_test_jovenpai_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_finetunning_test_jovenpai_en.md new file mode 100644 index 00000000000000..ef5149b8cd4d3c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_finetunning_test_jovenpai_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_finetunning_test_jovenpai BertForSequenceClassification from JovenPai +author: John Snow Labs +name: bert_finetunning_test_jovenpai +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetunning_test_jovenpai` is a English model originally trained by JovenPai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetunning_test_jovenpai_en_5.1.4_3.4_1698220026934.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetunning_test_jovenpai_en_5.1.4_3.4_1698220026934.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetunning_test_jovenpai","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetunning_test_jovenpai","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetunning_test_jovenpai| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/JovenPai/bert_finetunning_test \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_fom_job_description_assignment_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_fom_job_description_assignment_en.md new file mode 100644 index 00000000000000..659f75aa08ef65 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_fom_job_description_assignment_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_fom_job_description_assignment BertForSequenceClassification from Pazel +author: John Snow Labs +name: bert_fom_job_description_assignment +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_fom_job_description_assignment` is a English model originally trained by Pazel. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_fom_job_description_assignment_en_5.1.4_3.4_1698240255635.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_fom_job_description_assignment_en_5.1.4_3.4_1698240255635.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_fom_job_description_assignment","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_fom_job_description_assignment","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_fom_job_description_assignment| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|627.7 MB| + +## References + +https://huggingface.co/Pazel/bert-fom-job-description-assignment \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_for_pac_nl.md b/docs/_posts/ahmedlone127/2023-10-25-bert_for_pac_nl.md new file mode 100644 index 00000000000000..5fd004ed4173db --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_for_pac_nl.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Dutch, Flemish bert_for_pac BertForSequenceClassification from Gerwin +author: John Snow Labs +name: bert_for_pac +date: 2023-10-25 +tags: [bert, nl, open_source, sequence_classification, onnx] +task: Text Classification +language: nl +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_for_pac` is a Dutch, Flemish model originally trained by Gerwin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_for_pac_nl_5.1.4_3.4_1698204809405.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_for_pac_nl_5.1.4_3.4_1698204809405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_for_pac","nl")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_for_pac","nl") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_for_pac| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|nl| +|Size:|409.0 MB| + +## References + +https://huggingface.co/Gerwin/bert-for-pac \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_1_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_1_en.md new file mode 100644 index 00000000000000..f9b21706b2fc1a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_1_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_cola_1 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_cola_1 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_cola_1` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_cola_1_en_5.1.4_3.4_1698204051136.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_cola_1_en_5.1.4_3.4_1698204051136.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_1","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_1","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_cola_1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_cola-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_80_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_80_en.md new file mode 100644 index 00000000000000..a11758a4334828 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_80_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_cola_80 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_cola_80 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_cola_80` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_cola_80_en_5.1.4_3.4_1698223321437.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_cola_80_en_5.1.4_3.4_1698223321437.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_80","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_80","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_cola_80| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_cola-80 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_81_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_81_en.md new file mode 100644 index 00000000000000..8dca927e9d1e3b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_81_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_cola_81 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_cola_81 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_cola_81` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_cola_81_en_5.1.4_3.4_1698223539173.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_cola_81_en_5.1.4_3.4_1698223539173.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_81","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_81","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_cola_81| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_cola-81 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_82_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_82_en.md new file mode 100644 index 00000000000000..5eef4285deaf00 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_82_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_cola_82 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_cola_82 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_cola_82` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_cola_82_en_5.1.4_3.4_1698223738328.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_cola_82_en_5.1.4_3.4_1698223738328.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_82","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_82","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_cola_82| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_cola-82 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_83_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_83_en.md new file mode 100644 index 00000000000000..a3ca40a8535b14 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_83_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_cola_83 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_cola_83 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_cola_83` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_cola_83_en_5.1.4_3.4_1698223981519.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_cola_83_en_5.1.4_3.4_1698223981519.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_83","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_83","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_cola_83| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_cola-83 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_84_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_84_en.md new file mode 100644 index 00000000000000..bba56c7c70c7c7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_84_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_cola_84 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_cola_84 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_cola_84` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_cola_84_en_5.1.4_3.4_1698224151148.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_cola_84_en_5.1.4_3.4_1698224151148.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_84","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_84","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_cola_84| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_cola-84 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_85_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_85_en.md new file mode 100644 index 00000000000000..2c535953295c5e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_85_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_cola_85 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_cola_85 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_cola_85` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_cola_85_en_5.1.4_3.4_1698224389127.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_cola_85_en_5.1.4_3.4_1698224389127.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_85","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_85","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_cola_85| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_cola-85 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_86_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_86_en.md new file mode 100644 index 00000000000000..04c994e1e652fc --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_86_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_cola_86 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_cola_86 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_cola_86` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_cola_86_en_5.1.4_3.4_1698224587586.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_cola_86_en_5.1.4_3.4_1698224587586.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_86","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_86","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_cola_86| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_cola-86 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_87_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_87_en.md new file mode 100644 index 00000000000000..0892b6a6eb38ac --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_87_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_cola_87 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_cola_87 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_cola_87` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_cola_87_en_5.1.4_3.4_1698224817220.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_cola_87_en_5.1.4_3.4_1698224817220.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_87","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_87","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_cola_87| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_cola-87 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_88_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_88_en.md new file mode 100644 index 00000000000000..273bb864799e6e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_88_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_cola_88 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_cola_88 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_cola_88` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_cola_88_en_5.1.4_3.4_1698225043797.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_cola_88_en_5.1.4_3.4_1698225043797.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_88","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_88","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_cola_88| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_cola-88 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_89_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_89_en.md new file mode 100644 index 00000000000000..3d97ca2002d05c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_89_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_cola_89 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_cola_89 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_cola_89` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_cola_89_en_5.1.4_3.4_1698225941627.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_cola_89_en_5.1.4_3.4_1698225941627.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_89","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_89","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_cola_89| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_cola-89 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_90_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_90_en.md new file mode 100644 index 00000000000000..0dbfdf0e30c5e1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_90_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_cola_90 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_cola_90 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_cola_90` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_cola_90_en_5.1.4_3.4_1698226789555.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_cola_90_en_5.1.4_3.4_1698226789555.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_90","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_90","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_cola_90| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_cola-90 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_91_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_91_en.md new file mode 100644 index 00000000000000..03b02307627fca --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_91_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_cola_91 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_cola_91 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_cola_91` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_cola_91_en_5.1.4_3.4_1698227620626.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_cola_91_en_5.1.4_3.4_1698227620626.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_91","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_91","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_cola_91| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_cola-91 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_92_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_92_en.md new file mode 100644 index 00000000000000..399837865a7ada --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_92_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_cola_92 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_cola_92 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_cola_92` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_cola_92_en_5.1.4_3.4_1698228298225.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_cola_92_en_5.1.4_3.4_1698228298225.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_92","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_92","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_cola_92| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_cola-92 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_93_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_93_en.md new file mode 100644 index 00000000000000..6aa06d646ead45 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_93_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_cola_93 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_cola_93 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_cola_93` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_cola_93_en_5.1.4_3.4_1698229260438.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_cola_93_en_5.1.4_3.4_1698229260438.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_93","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_93","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_cola_93| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_cola-93 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_94_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_94_en.md new file mode 100644 index 00000000000000..b42bb56a7fe310 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_94_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_cola_94 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_cola_94 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_cola_94` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_cola_94_en_5.1.4_3.4_1698230141395.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_cola_94_en_5.1.4_3.4_1698230141395.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_94","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_94","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_cola_94| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_cola-94 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_95_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_95_en.md new file mode 100644 index 00000000000000..429efe7c6a856a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_95_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_cola_95 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_cola_95 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_cola_95` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_cola_95_en_5.1.4_3.4_1698230908873.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_cola_95_en_5.1.4_3.4_1698230908873.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_95","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_95","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_cola_95| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_cola-95 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_96_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_96_en.md new file mode 100644 index 00000000000000..ad2da76485c85f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_96_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_cola_96 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_cola_96 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_cola_96` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_cola_96_en_5.1.4_3.4_1698231828253.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_cola_96_en_5.1.4_3.4_1698231828253.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_96","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_96","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_cola_96| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_cola-96 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_97_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_97_en.md new file mode 100644 index 00000000000000..3fe7a26782da02 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_97_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_cola_97 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_cola_97 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_cola_97` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_cola_97_en_5.1.4_3.4_1698232593733.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_cola_97_en_5.1.4_3.4_1698232593733.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_97","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_97","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_cola_97| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_cola-97 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_98_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_98_en.md new file mode 100644 index 00000000000000..66a9f195cc2db1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_98_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_cola_98 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_cola_98 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_cola_98` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_cola_98_en_5.1.4_3.4_1698233424850.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_cola_98_en_5.1.4_3.4_1698233424850.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_98","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_98","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_cola_98| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_cola-98 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_99_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_99_en.md new file mode 100644 index 00000000000000..628c3fa60b2503 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_cola_99_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_cola_99 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_cola_99 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_cola_99` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_cola_99_en_5.1.4_3.4_1698234234091.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_cola_99_en_5.1.4_3.4_1698234234091.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_99","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_cola_99","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_cola_99| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_cola-99 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_0_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_0_jeevesh8_en.md new file mode 100644 index 00000000000000..fd40c2b56cce42 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_0_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_0_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_0_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_0_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_0_jeevesh8_en_5.1.4_3.4_1698203592878.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_0_jeevesh8_en_5.1.4_3.4_1698203592878.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_0_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_0_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_0_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_10_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_10_jeevesh8_en.md new file mode 100644 index 00000000000000..a92057dd812b04 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_10_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_10_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_10_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_10_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_10_jeevesh8_en_5.1.4_3.4_1698205946880.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_10_jeevesh8_en_5.1.4_3.4_1698205946880.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_10_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_10_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_10_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_11_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_11_jeevesh8_en.md new file mode 100644 index 00000000000000..df1edea4a1376f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_11_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_11_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_11_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_11_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_11_jeevesh8_en_5.1.4_3.4_1698206127191.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_11_jeevesh8_en_5.1.4_3.4_1698206127191.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_11_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_11_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_11_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-11 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_12_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_12_jeevesh8_en.md new file mode 100644 index 00000000000000..b28d8360ab2e9a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_12_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_12_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_12_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_12_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_12_jeevesh8_en_5.1.4_3.4_1698206312706.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_12_jeevesh8_en_5.1.4_3.4_1698206312706.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_12_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_12_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_12_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-12 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_13_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_13_jeevesh8_en.md new file mode 100644 index 00000000000000..3b9d7649652dcc --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_13_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_13_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_13_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_13_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_13_jeevesh8_en_5.1.4_3.4_1698206499211.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_13_jeevesh8_en_5.1.4_3.4_1698206499211.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_13_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_13_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_13_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-13 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_14_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_14_jeevesh8_en.md new file mode 100644 index 00000000000000..34d2566a29bba1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_14_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_14_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_14_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_14_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_14_jeevesh8_en_5.1.4_3.4_1698206689015.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_14_jeevesh8_en_5.1.4_3.4_1698206689015.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_14_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_14_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_14_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-14 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_15_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_15_jeevesh8_en.md new file mode 100644 index 00000000000000..3b4a0399267c9d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_15_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_15_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_15_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_15_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_15_jeevesh8_en_5.1.4_3.4_1698206892996.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_15_jeevesh8_en_5.1.4_3.4_1698206892996.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_15_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_15_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_15_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-15 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_16_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_16_jeevesh8_en.md new file mode 100644 index 00000000000000..164a09e5075538 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_16_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_16_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_16_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_16_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_16_jeevesh8_en_5.1.4_3.4_1698207096253.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_16_jeevesh8_en_5.1.4_3.4_1698207096253.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_16_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_16_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_16_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-16 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_17_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_17_jeevesh8_en.md new file mode 100644 index 00000000000000..6ae84e22abfd9e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_17_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_17_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_17_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_17_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_17_jeevesh8_en_5.1.4_3.4_1698207287384.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_17_jeevesh8_en_5.1.4_3.4_1698207287384.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_17_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_17_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_17_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-17 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_18_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_18_jeevesh8_en.md new file mode 100644 index 00000000000000..5636da9949ad10 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_18_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_18_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_18_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_18_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_18_jeevesh8_en_5.1.4_3.4_1698207518024.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_18_jeevesh8_en_5.1.4_3.4_1698207518024.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_18_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_18_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_18_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-18 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_19_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_19_jeevesh8_en.md new file mode 100644 index 00000000000000..a40c57576230db --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_19_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_19_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_19_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_19_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_19_jeevesh8_en_5.1.4_3.4_1698207755851.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_19_jeevesh8_en_5.1.4_3.4_1698207755851.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_19_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_19_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_19_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-19 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_1_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_1_jeevesh8_en.md new file mode 100644 index 00000000000000..cbe72184678aa2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_1_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_1_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_1_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_1_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_1_jeevesh8_en_5.1.4_3.4_1698204232841.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_1_jeevesh8_en_5.1.4_3.4_1698204232841.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_1_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_1_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_1_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_20_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_20_jeevesh8_en.md new file mode 100644 index 00000000000000..441227b92234f2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_20_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_20_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_20_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_20_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_20_jeevesh8_en_5.1.4_3.4_1698207967403.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_20_jeevesh8_en_5.1.4_3.4_1698207967403.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_20_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_20_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_20_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-20 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_21_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_21_jeevesh8_en.md new file mode 100644 index 00000000000000..9ca5d3369483e7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_21_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_21_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_21_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_21_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_21_jeevesh8_en_5.1.4_3.4_1698208211620.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_21_jeevesh8_en_5.1.4_3.4_1698208211620.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_21_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_21_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_21_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-21 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_22_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_22_jeevesh8_en.md new file mode 100644 index 00000000000000..5ba6dc6d6f5c3b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_22_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_22_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_22_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_22_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_22_jeevesh8_en_5.1.4_3.4_1698208388737.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_22_jeevesh8_en_5.1.4_3.4_1698208388737.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_22_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_22_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_22_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-22 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_23_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_23_jeevesh8_en.md new file mode 100644 index 00000000000000..8e10b6d7641a9d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_23_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_23_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_23_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_23_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_23_jeevesh8_en_5.1.4_3.4_1698208563784.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_23_jeevesh8_en_5.1.4_3.4_1698208563784.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_23_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_23_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_23_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-23 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_24_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_24_jeevesh8_en.md new file mode 100644 index 00000000000000..148e66ddfc49ad --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_24_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_24_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_24_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_24_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_24_jeevesh8_en_5.1.4_3.4_1698208744152.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_24_jeevesh8_en_5.1.4_3.4_1698208744152.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_24_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_24_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_24_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-24 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_25_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_25_jeevesh8_en.md new file mode 100644 index 00000000000000..ddeb8731a755cf --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_25_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_25_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_25_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_25_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_25_jeevesh8_en_5.1.4_3.4_1698208915416.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_25_jeevesh8_en_5.1.4_3.4_1698208915416.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_25_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_25_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_25_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-25 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_26_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_26_jeevesh8_en.md new file mode 100644 index 00000000000000..99e7829ad3ec4b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_26_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_26_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_26_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_26_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_26_jeevesh8_en_5.1.4_3.4_1698209089585.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_26_jeevesh8_en_5.1.4_3.4_1698209089585.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_26_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_26_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_26_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-26 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_27_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_27_jeevesh8_en.md new file mode 100644 index 00000000000000..07893b82943194 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_27_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_27_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_27_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_27_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_27_jeevesh8_en_5.1.4_3.4_1698209273711.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_27_jeevesh8_en_5.1.4_3.4_1698209273711.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_27_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_27_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_27_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-27 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_28_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_28_jeevesh8_en.md new file mode 100644 index 00000000000000..b1dd43fc162443 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_28_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_28_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_28_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_28_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_28_jeevesh8_en_5.1.4_3.4_1698209449348.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_28_jeevesh8_en_5.1.4_3.4_1698209449348.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_28_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_28_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_28_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-28 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_29_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_29_jeevesh8_en.md new file mode 100644 index 00000000000000..d85188a4da4b91 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_29_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_29_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_29_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_29_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_29_jeevesh8_en_5.1.4_3.4_1698209636455.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_29_jeevesh8_en_5.1.4_3.4_1698209636455.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_29_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_29_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_29_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-29 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_2_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_2_jeevesh8_en.md new file mode 100644 index 00000000000000..de775ad8c1ab3f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_2_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_2_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_2_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_2_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_2_jeevesh8_en_5.1.4_3.4_1698204420000.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_2_jeevesh8_en_5.1.4_3.4_1698204420000.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_2_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_2_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_2_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_30_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_30_jeevesh8_en.md new file mode 100644 index 00000000000000..f7407064f08816 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_30_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_30_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_30_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_30_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_30_jeevesh8_en_5.1.4_3.4_1698209832868.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_30_jeevesh8_en_5.1.4_3.4_1698209832868.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_30_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_30_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_30_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-30 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_31_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_31_jeevesh8_en.md new file mode 100644 index 00000000000000..18fca0704094bb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_31_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_31_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_31_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_31_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_31_jeevesh8_en_5.1.4_3.4_1698209991407.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_31_jeevesh8_en_5.1.4_3.4_1698209991407.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_31_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_31_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_31_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-31 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_32_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_32_jeevesh8_en.md new file mode 100644 index 00000000000000..32f97dee543e44 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_32_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_32_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_32_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_32_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_32_jeevesh8_en_5.1.4_3.4_1698210183570.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_32_jeevesh8_en_5.1.4_3.4_1698210183570.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_32_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_32_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_32_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-32 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_33_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_33_jeevesh8_en.md new file mode 100644 index 00000000000000..f1e443cdd98700 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_33_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_33_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_33_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_33_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_33_jeevesh8_en_5.1.4_3.4_1698210374266.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_33_jeevesh8_en_5.1.4_3.4_1698210374266.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_33_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_33_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_33_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-33 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_34_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_34_jeevesh8_en.md new file mode 100644 index 00000000000000..8330425469eb9e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_34_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_34_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_34_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_34_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_34_jeevesh8_en_5.1.4_3.4_1698210562574.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_34_jeevesh8_en_5.1.4_3.4_1698210562574.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_34_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_34_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_34_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-34 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_35_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_35_jeevesh8_en.md new file mode 100644 index 00000000000000..5255680f088f1c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_35_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_35_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_35_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_35_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_35_jeevesh8_en_5.1.4_3.4_1698210737122.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_35_jeevesh8_en_5.1.4_3.4_1698210737122.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_35_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_35_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_35_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-35 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_36_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_36_jeevesh8_en.md new file mode 100644 index 00000000000000..fd58f173f8acd5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_36_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_36_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_36_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_36_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_36_jeevesh8_en_5.1.4_3.4_1698210931104.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_36_jeevesh8_en_5.1.4_3.4_1698210931104.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_36_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_36_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_36_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-36 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_37_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_37_jeevesh8_en.md new file mode 100644 index 00000000000000..03aaedc6d91ed0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_37_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_37_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_37_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_37_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_37_jeevesh8_en_5.1.4_3.4_1698211116252.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_37_jeevesh8_en_5.1.4_3.4_1698211116252.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_37_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_37_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_37_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-37 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_38_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_38_jeevesh8_en.md new file mode 100644 index 00000000000000..66c21265c34ccb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_38_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_38_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_38_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_38_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_38_jeevesh8_en_5.1.4_3.4_1698211283214.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_38_jeevesh8_en_5.1.4_3.4_1698211283214.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_38_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_38_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_38_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-38 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_39_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_39_jeevesh8_en.md new file mode 100644 index 00000000000000..4492e5b16263eb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_39_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_39_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_39_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_39_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_39_jeevesh8_en_5.1.4_3.4_1698211490664.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_39_jeevesh8_en_5.1.4_3.4_1698211490664.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_39_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_39_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_39_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-39 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_3_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_3_jeevesh8_en.md new file mode 100644 index 00000000000000..9d2958d6a1cc2f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_3_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_3_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_3_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_3_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_3_jeevesh8_en_5.1.4_3.4_1698204610936.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_3_jeevesh8_en_5.1.4_3.4_1698204610936.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_3_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_3_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_3_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_40_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_40_jeevesh8_en.md new file mode 100644 index 00000000000000..2bcb77a1b79224 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_40_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_40_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_40_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_40_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_40_jeevesh8_en_5.1.4_3.4_1698211661814.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_40_jeevesh8_en_5.1.4_3.4_1698211661814.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_40_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_40_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_40_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-40 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_41_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_41_jeevesh8_en.md new file mode 100644 index 00000000000000..2fbc54490a101a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_41_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_41_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_41_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_41_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_41_jeevesh8_en_5.1.4_3.4_1698211837919.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_41_jeevesh8_en_5.1.4_3.4_1698211837919.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_41_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_41_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_41_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-41 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_42_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_42_jeevesh8_en.md new file mode 100644 index 00000000000000..6e8cd8ba73b5c0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_42_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_42_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_42_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_42_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_42_jeevesh8_en_5.1.4_3.4_1698212046210.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_42_jeevesh8_en_5.1.4_3.4_1698212046210.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_42_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_42_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_42_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-42 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_43_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_43_jeevesh8_en.md new file mode 100644 index 00000000000000..ab6606d2897fe1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_43_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_43_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_43_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_43_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_43_jeevesh8_en_5.1.4_3.4_1698212258279.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_43_jeevesh8_en_5.1.4_3.4_1698212258279.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_43_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_43_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_43_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-43 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_44_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_44_jeevesh8_en.md new file mode 100644 index 00000000000000..5af2d3af8f2aeb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_44_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_44_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_44_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_44_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_44_jeevesh8_en_5.1.4_3.4_1698212459706.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_44_jeevesh8_en_5.1.4_3.4_1698212459706.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_44_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_44_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_44_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-44 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_45_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_45_jeevesh8_en.md new file mode 100644 index 00000000000000..76a4bbff36664a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_45_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_45_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_45_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_45_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_45_jeevesh8_en_5.1.4_3.4_1698212646870.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_45_jeevesh8_en_5.1.4_3.4_1698212646870.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_45_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_45_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_45_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-45 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_46_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_46_jeevesh8_en.md new file mode 100644 index 00000000000000..93434b5b041dce --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_46_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_46_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_46_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_46_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_46_jeevesh8_en_5.1.4_3.4_1698212811977.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_46_jeevesh8_en_5.1.4_3.4_1698212811977.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_46_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_46_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_46_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-46 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_47_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_47_jeevesh8_en.md new file mode 100644 index 00000000000000..e2cd239cc85577 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_47_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_47_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_47_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_47_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_47_jeevesh8_en_5.1.4_3.4_1698213009569.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_47_jeevesh8_en_5.1.4_3.4_1698213009569.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_47_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_47_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_47_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-47 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_48_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_48_jeevesh8_en.md new file mode 100644 index 00000000000000..0b9fb40ae5fb5c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_48_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_48_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_48_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_48_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_48_jeevesh8_en_5.1.4_3.4_1698213183262.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_48_jeevesh8_en_5.1.4_3.4_1698213183262.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_48_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_48_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_48_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-48 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_49_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_49_jeevesh8_en.md new file mode 100644 index 00000000000000..1301a3d3b1bda6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_49_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_49_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_49_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_49_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_49_jeevesh8_en_5.1.4_3.4_1698213351499.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_49_jeevesh8_en_5.1.4_3.4_1698213351499.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_49_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_49_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_49_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-49 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_4_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_4_jeevesh8_en.md new file mode 100644 index 00000000000000..1cf08a09656a41 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_4_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_4_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_4_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_4_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_4_jeevesh8_en_5.1.4_3.4_1698204829567.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_4_jeevesh8_en_5.1.4_3.4_1698204829567.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_4_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_4_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_4_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_50_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_50_jeevesh8_en.md new file mode 100644 index 00000000000000..3c78b5d05dc2bf --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_50_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_50_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_50_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_50_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_50_jeevesh8_en_5.1.4_3.4_1698213522662.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_50_jeevesh8_en_5.1.4_3.4_1698213522662.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_50_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_50_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_50_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-50 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_51_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_51_jeevesh8_en.md new file mode 100644 index 00000000000000..18968564b326dc --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_51_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_51_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_51_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_51_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_51_jeevesh8_en_5.1.4_3.4_1698213702714.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_51_jeevesh8_en_5.1.4_3.4_1698213702714.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_51_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_51_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_51_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-51 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_52_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_52_jeevesh8_en.md new file mode 100644 index 00000000000000..cfc8b90c280ca1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_52_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_52_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_52_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_52_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_52_jeevesh8_en_5.1.4_3.4_1698213920269.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_52_jeevesh8_en_5.1.4_3.4_1698213920269.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_52_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_52_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_52_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-52 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_53_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_53_jeevesh8_en.md new file mode 100644 index 00000000000000..0e7b90981d9a9d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_53_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_53_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_53_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_53_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_53_jeevesh8_en_5.1.4_3.4_1698214108834.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_53_jeevesh8_en_5.1.4_3.4_1698214108834.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_53_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_53_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_53_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-53 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_54_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_54_jeevesh8_en.md new file mode 100644 index 00000000000000..b35491e1ee11ec --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_54_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_54_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_54_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_54_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_54_jeevesh8_en_5.1.4_3.4_1698214298205.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_54_jeevesh8_en_5.1.4_3.4_1698214298205.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_54_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_54_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_54_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-54 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_55_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_55_jeevesh8_en.md new file mode 100644 index 00000000000000..010d33b0f4687c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_55_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_55_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_55_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_55_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_55_jeevesh8_en_5.1.4_3.4_1698214456511.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_55_jeevesh8_en_5.1.4_3.4_1698214456511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_55_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_55_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_55_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-55 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_56_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_56_jeevesh8_en.md new file mode 100644 index 00000000000000..c733153ce00af4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_56_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_56_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_56_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_56_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_56_jeevesh8_en_5.1.4_3.4_1698214624241.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_56_jeevesh8_en_5.1.4_3.4_1698214624241.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_56_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_56_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_56_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-56 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_57_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_57_jeevesh8_en.md new file mode 100644 index 00000000000000..725a89b01ea523 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_57_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_57_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_57_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_57_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_57_jeevesh8_en_5.1.4_3.4_1698214829790.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_57_jeevesh8_en_5.1.4_3.4_1698214829790.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_57_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_57_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_57_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-57 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_58_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_58_jeevesh8_en.md new file mode 100644 index 00000000000000..36d2d688310ea4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_58_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_58_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_58_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_58_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_58_jeevesh8_en_5.1.4_3.4_1698215018977.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_58_jeevesh8_en_5.1.4_3.4_1698215018977.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_58_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_58_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_58_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-58 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_59_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_59_jeevesh8_en.md new file mode 100644 index 00000000000000..0b9bc48e44cd70 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_59_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_59_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_59_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_59_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_59_jeevesh8_en_5.1.4_3.4_1698215223743.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_59_jeevesh8_en_5.1.4_3.4_1698215223743.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_59_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_59_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_59_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-59 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_5_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_5_jeevesh8_en.md new file mode 100644 index 00000000000000..07a3667736a558 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_5_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_5_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_5_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_5_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_5_jeevesh8_en_5.1.4_3.4_1698205035497.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_5_jeevesh8_en_5.1.4_3.4_1698205035497.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_5_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_5_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_5_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_60_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_60_jeevesh8_en.md new file mode 100644 index 00000000000000..3eafab9744c5f4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_60_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_60_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_60_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_60_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_60_jeevesh8_en_5.1.4_3.4_1698215414427.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_60_jeevesh8_en_5.1.4_3.4_1698215414427.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_60_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_60_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_60_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-60 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_61_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_61_jeevesh8_en.md new file mode 100644 index 00000000000000..2e1a12c9430fe3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_61_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_61_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_61_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_61_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_61_jeevesh8_en_5.1.4_3.4_1698215638548.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_61_jeevesh8_en_5.1.4_3.4_1698215638548.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_61_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_61_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_61_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-61 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_62_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_62_jeevesh8_en.md new file mode 100644 index 00000000000000..77b77be0520796 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_62_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_62_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_62_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_62_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_62_jeevesh8_en_5.1.4_3.4_1698215835889.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_62_jeevesh8_en_5.1.4_3.4_1698215835889.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_62_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_62_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_62_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-62 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_63_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_63_jeevesh8_en.md new file mode 100644 index 00000000000000..e889680e085936 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_63_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_63_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_63_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_63_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_63_jeevesh8_en_5.1.4_3.4_1698216072292.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_63_jeevesh8_en_5.1.4_3.4_1698216072292.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_63_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_63_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_63_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-63 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_64_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_64_jeevesh8_en.md new file mode 100644 index 00000000000000..41b955f83abbaa --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_64_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_64_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_64_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_64_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_64_jeevesh8_en_5.1.4_3.4_1698216257062.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_64_jeevesh8_en_5.1.4_3.4_1698216257062.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_64_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_64_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_64_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-64 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_65_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_65_jeevesh8_en.md new file mode 100644 index 00000000000000..1ce4c579d098e5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_65_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_65_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_65_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_65_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_65_jeevesh8_en_5.1.4_3.4_1698216457035.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_65_jeevesh8_en_5.1.4_3.4_1698216457035.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_65_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_65_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_65_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-65 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_66_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_66_jeevesh8_en.md new file mode 100644 index 00000000000000..27fac2a0ae0207 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_66_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_66_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_66_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_66_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_66_jeevesh8_en_5.1.4_3.4_1698216620636.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_66_jeevesh8_en_5.1.4_3.4_1698216620636.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_66_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_66_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_66_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-66 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_67_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_67_jeevesh8_en.md new file mode 100644 index 00000000000000..eae3c73f4f9f0e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_67_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_67_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_67_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_67_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_67_jeevesh8_en_5.1.4_3.4_1698216795716.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_67_jeevesh8_en_5.1.4_3.4_1698216795716.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_67_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_67_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_67_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-67 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_68_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_68_jeevesh8_en.md new file mode 100644 index 00000000000000..06c843a9e74b16 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_68_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_68_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_68_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_68_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_68_jeevesh8_en_5.1.4_3.4_1698217001117.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_68_jeevesh8_en_5.1.4_3.4_1698217001117.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_68_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_68_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_68_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-68 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_69_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_69_jeevesh8_en.md new file mode 100644 index 00000000000000..9cce706ffa0aec --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_69_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_69_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_69_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_69_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_69_jeevesh8_en_5.1.4_3.4_1698217190353.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_69_jeevesh8_en_5.1.4_3.4_1698217190353.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_69_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_69_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_69_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-69 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_6_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_6_jeevesh8_en.md new file mode 100644 index 00000000000000..68ec5ec38c6f42 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_6_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_6_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_6_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_6_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_6_jeevesh8_en_5.1.4_3.4_1698205246513.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_6_jeevesh8_en_5.1.4_3.4_1698205246513.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_6_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_6_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_6_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_70_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_70_jeevesh8_en.md new file mode 100644 index 00000000000000..d4bd1e1d1d9d9e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_70_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_70_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_70_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_70_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_70_jeevesh8_en_5.1.4_3.4_1698217393089.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_70_jeevesh8_en_5.1.4_3.4_1698217393089.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_70_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_70_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_70_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-70 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_71_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_71_jeevesh8_en.md new file mode 100644 index 00000000000000..3ce95967034753 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_71_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_71_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_71_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_71_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_71_jeevesh8_en_5.1.4_3.4_1698217576041.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_71_jeevesh8_en_5.1.4_3.4_1698217576041.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_71_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_71_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_71_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-71 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_72_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_72_jeevesh8_en.md new file mode 100644 index 00000000000000..825dee7b6c2872 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_72_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_72_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_72_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_72_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_72_jeevesh8_en_5.1.4_3.4_1698217803909.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_72_jeevesh8_en_5.1.4_3.4_1698217803909.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_72_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_72_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_72_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-72 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_73_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_73_jeevesh8_en.md new file mode 100644 index 00000000000000..44602a69184f7c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_73_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_73_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_73_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_73_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_73_jeevesh8_en_5.1.4_3.4_1698218011258.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_73_jeevesh8_en_5.1.4_3.4_1698218011258.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_73_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_73_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_73_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-73 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_74_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_74_jeevesh8_en.md new file mode 100644 index 00000000000000..6a41d5c80afd44 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_74_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_74_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_74_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_74_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_74_jeevesh8_en_5.1.4_3.4_1698218235028.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_74_jeevesh8_en_5.1.4_3.4_1698218235028.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_74_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_74_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_74_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-74 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_75_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_75_jeevesh8_en.md new file mode 100644 index 00000000000000..43eb52676b0869 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_75_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_75_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_75_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_75_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_75_jeevesh8_en_5.1.4_3.4_1698218407337.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_75_jeevesh8_en_5.1.4_3.4_1698218407337.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_75_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_75_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_75_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-75 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_76_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_76_jeevesh8_en.md new file mode 100644 index 00000000000000..73fc21ae970d18 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_76_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_76_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_76_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_76_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_76_jeevesh8_en_5.1.4_3.4_1698218619964.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_76_jeevesh8_en_5.1.4_3.4_1698218619964.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_76_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_76_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_76_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-76 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_77_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_77_jeevesh8_en.md new file mode 100644 index 00000000000000..e286b0611a9ece --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_77_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_77_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_77_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_77_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_77_jeevesh8_en_5.1.4_3.4_1698218842115.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_77_jeevesh8_en_5.1.4_3.4_1698218842115.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_77_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_77_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_77_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-77 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_78_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_78_jeevesh8_en.md new file mode 100644 index 00000000000000..7241bbde425e57 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_78_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_78_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_78_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_78_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_78_jeevesh8_en_5.1.4_3.4_1698219051215.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_78_jeevesh8_en_5.1.4_3.4_1698219051215.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_78_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_78_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_78_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-78 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_79_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_79_jeevesh8_en.md new file mode 100644 index 00000000000000..4c5c45e5978045 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_79_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_79_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_79_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_79_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_79_jeevesh8_en_5.1.4_3.4_1698219225696.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_79_jeevesh8_en_5.1.4_3.4_1698219225696.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_79_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_79_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_79_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-79 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_7_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_7_jeevesh8_en.md new file mode 100644 index 00000000000000..7e9d290f3d0a36 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_7_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_7_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_7_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_7_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_7_jeevesh8_en_5.1.4_3.4_1698205437574.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_7_jeevesh8_en_5.1.4_3.4_1698205437574.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_7_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_7_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_7_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-7 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_80_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_80_jeevesh8_en.md new file mode 100644 index 00000000000000..d6625282269809 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_80_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_80_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_80_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_80_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_80_jeevesh8_en_5.1.4_3.4_1698219407321.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_80_jeevesh8_en_5.1.4_3.4_1698219407321.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_80_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_80_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_80_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-80 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_81_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_81_jeevesh8_en.md new file mode 100644 index 00000000000000..ed95812dd8dbe0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_81_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_81_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_81_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_81_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_81_jeevesh8_en_5.1.4_3.4_1698219587212.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_81_jeevesh8_en_5.1.4_3.4_1698219587212.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_81_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_81_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_81_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-81 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_82_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_82_jeevesh8_en.md new file mode 100644 index 00000000000000..fed0cb005da5c4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_82_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_82_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_82_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_82_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_82_jeevesh8_en_5.1.4_3.4_1698219788884.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_82_jeevesh8_en_5.1.4_3.4_1698219788884.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_82_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_82_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_82_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-82 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_83_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_83_jeevesh8_en.md new file mode 100644 index 00000000000000..d199f7ff7379dc --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_83_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_83_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_83_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_83_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_83_jeevesh8_en_5.1.4_3.4_1698219977145.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_83_jeevesh8_en_5.1.4_3.4_1698219977145.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_83_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_83_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_83_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-83 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_84_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_84_jeevesh8_en.md new file mode 100644 index 00000000000000..db8311cb113793 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_84_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_84_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_84_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_84_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_84_jeevesh8_en_5.1.4_3.4_1698220142773.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_84_jeevesh8_en_5.1.4_3.4_1698220142773.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_84_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_84_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_84_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-84 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_85_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_85_jeevesh8_en.md new file mode 100644 index 00000000000000..b6b91b836dafc4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_85_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_85_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_85_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_85_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_85_jeevesh8_en_5.1.4_3.4_1698220376391.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_85_jeevesh8_en_5.1.4_3.4_1698220376391.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_85_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_85_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_85_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-85 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_86_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_86_jeevesh8_en.md new file mode 100644 index 00000000000000..6c1a72f86b478d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_86_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_86_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_86_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_86_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_86_jeevesh8_en_5.1.4_3.4_1698220562838.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_86_jeevesh8_en_5.1.4_3.4_1698220562838.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_86_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_86_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_86_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-86 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_87_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_87_jeevesh8_en.md new file mode 100644 index 00000000000000..bec5d19ff4e595 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_87_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_87_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_87_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_87_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_87_jeevesh8_en_5.1.4_3.4_1698220763383.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_87_jeevesh8_en_5.1.4_3.4_1698220763383.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_87_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_87_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_87_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-87 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_88_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_88_jeevesh8_en.md new file mode 100644 index 00000000000000..e8a257a0cec721 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_88_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_88_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_88_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_88_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_88_jeevesh8_en_5.1.4_3.4_1698220946763.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_88_jeevesh8_en_5.1.4_3.4_1698220946763.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_88_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_88_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_88_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-88 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_89_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_89_jeevesh8_en.md new file mode 100644 index 00000000000000..154c0757ad2f48 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_89_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_89_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_89_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_89_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_89_jeevesh8_en_5.1.4_3.4_1698221153353.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_89_jeevesh8_en_5.1.4_3.4_1698221153353.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_89_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_89_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_89_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-89 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_8_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_8_jeevesh8_en.md new file mode 100644 index 00000000000000..1667b37b671aff --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_8_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_8_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_8_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_8_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_8_jeevesh8_en_5.1.4_3.4_1698205615887.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_8_jeevesh8_en_5.1.4_3.4_1698205615887.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_8_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_8_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_8_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_90_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_90_jeevesh8_en.md new file mode 100644 index 00000000000000..b87c08c17e7577 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_90_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_90_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_90_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_90_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_90_jeevesh8_en_5.1.4_3.4_1698221354382.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_90_jeevesh8_en_5.1.4_3.4_1698221354382.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_90_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_90_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_90_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-90 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_91_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_91_jeevesh8_en.md new file mode 100644 index 00000000000000..5d572e035ecb56 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_91_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_91_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_91_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_91_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_91_jeevesh8_en_5.1.4_3.4_1698221523166.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_91_jeevesh8_en_5.1.4_3.4_1698221523166.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_91_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_91_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_91_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-91 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_92_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_92_jeevesh8_en.md new file mode 100644 index 00000000000000..dc9a643130d58b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_92_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_92_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_92_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_92_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_92_jeevesh8_en_5.1.4_3.4_1698221750750.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_92_jeevesh8_en_5.1.4_3.4_1698221750750.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_92_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_92_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_92_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-92 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_93_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_93_jeevesh8_en.md new file mode 100644 index 00000000000000..5ad503ad756a17 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_93_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_93_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_93_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_93_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_93_jeevesh8_en_5.1.4_3.4_1698221927847.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_93_jeevesh8_en_5.1.4_3.4_1698221927847.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_93_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_93_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_93_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-93 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_94_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_94_jeevesh8_en.md new file mode 100644 index 00000000000000..2482eea032a407 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_94_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_94_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_94_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_94_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_94_jeevesh8_en_5.1.4_3.4_1698222116709.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_94_jeevesh8_en_5.1.4_3.4_1698222116709.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_94_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_94_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_94_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-94 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_95_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_95_jeevesh8_en.md new file mode 100644 index 00000000000000..aed86d7d67f013 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_95_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_95_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_95_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_95_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_95_jeevesh8_en_5.1.4_3.4_1698222330820.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_95_jeevesh8_en_5.1.4_3.4_1698222330820.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_95_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_95_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_95_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-95 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_96_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_96_jeevesh8_en.md new file mode 100644 index 00000000000000..6a4460720fd2e1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_96_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_96_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_96_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_96_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_96_jeevesh8_en_5.1.4_3.4_1698222552917.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_96_jeevesh8_en_5.1.4_3.4_1698222552917.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_96_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_96_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_96_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-96 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_97_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_97_jeevesh8_en.md new file mode 100644 index 00000000000000..903dcfcb641ca0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_97_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_97_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_97_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_97_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_97_jeevesh8_en_5.1.4_3.4_1698222743039.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_97_jeevesh8_en_5.1.4_3.4_1698222743039.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_97_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_97_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_97_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-97 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_98_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_98_jeevesh8_en.md new file mode 100644 index 00000000000000..a26be80333e374 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_98_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_98_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_98_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_98_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_98_jeevesh8_en_5.1.4_3.4_1698222930954.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_98_jeevesh8_en_5.1.4_3.4_1698222930954.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_98_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_98_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_98_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-98 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_99_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_99_jeevesh8_en.md new file mode 100644 index 00000000000000..cf663bca885066 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_99_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_99_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_99_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_99_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_99_jeevesh8_en_5.1.4_3.4_1698223118980.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_99_jeevesh8_en_5.1.4_3.4_1698223118980.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_99_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_99_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_99_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-99 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_9_jeevesh8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_9_jeevesh8_en.md new file mode 100644 index 00000000000000..7b436fa04aad56 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_ft_qqp_9_jeevesh8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_ft_qqp_9_jeevesh8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: bert_ft_qqp_9_jeevesh8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_ft_qqp_9_jeevesh8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_9_jeevesh8_en_5.1.4_3.4_1698205770457.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_ft_qqp_9_jeevesh8_en_5.1.4_3.4_1698205770457.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_9_jeevesh8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_ft_qqp_9_jeevesh8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_ft_qqp_9_jeevesh8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/bert_ft_qqp-9 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_iphone_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_iphone_en.md new file mode 100644 index 00000000000000..1673ce96dc18f1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_iphone_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_iphone BertForSequenceClassification from konrad-wesub +author: John Snow Labs +name: bert_iphone +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_iphone` is a English model originally trained by konrad-wesub. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_iphone_en_5.1.4_3.4_1698197859635.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_iphone_en_5.1.4_3.4_1698197859635.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_iphone","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_iphone","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_iphone| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|667.3 MB| + +## References + +https://huggingface.co/konrad-wesub/bert-iphone \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_italian_emotion_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_italian_emotion_en.md new file mode 100644 index 00000000000000..b76d0f2c0bd357 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_italian_emotion_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_italian_emotion BertForSequenceClassification from pysentimiento +author: John Snow Labs +name: bert_italian_emotion +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_italian_emotion` is a English model originally trained by pysentimiento. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_italian_emotion_en_5.1.4_3.4_1698221965080.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_italian_emotion_en_5.1.4_3.4_1698221965080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_italian_emotion","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_italian_emotion","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_italian_emotion| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.9 MB| + +## References + +https://huggingface.co/pysentimiento/bert-it-emotion \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_italian_hate_speech_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_italian_hate_speech_en.md new file mode 100644 index 00000000000000..4ecf9e8b7aa01c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_italian_hate_speech_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_italian_hate_speech BertForSequenceClassification from pysentimiento +author: John Snow Labs +name: bert_italian_hate_speech +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_italian_hate_speech` is a English model originally trained by pysentimiento. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_italian_hate_speech_en_5.1.4_3.4_1698222151141.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_italian_hate_speech_en_5.1.4_3.4_1698222151141.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_italian_hate_speech","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_italian_hate_speech","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_italian_hate_speech| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.9 MB| + +## References + +https://huggingface.co/pysentimiento/bert-it-hate-speech \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_italian_irony_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_italian_irony_en.md new file mode 100644 index 00000000000000..8ecdc13462ecf9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_italian_irony_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_italian_irony BertForSequenceClassification from pysentimiento +author: John Snow Labs +name: bert_italian_irony +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_italian_irony` is a English model originally trained by pysentimiento. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_italian_irony_en_5.1.4_3.4_1698222335196.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_italian_irony_en_5.1.4_3.4_1698222335196.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_italian_irony","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_italian_irony","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_italian_irony| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.9 MB| + +## References + +https://huggingface.co/pysentimiento/bert-it-irony \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_italian_sentiment_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_italian_sentiment_en.md new file mode 100644 index 00000000000000..6b6a48ceebb185 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_italian_sentiment_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_italian_sentiment BertForSequenceClassification from pysentimiento +author: John Snow Labs +name: bert_italian_sentiment +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_italian_sentiment` is a English model originally trained by pysentimiento. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_italian_sentiment_en_5.1.4_3.4_1698221577302.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_italian_sentiment_en_5.1.4_3.4_1698221577302.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_italian_sentiment","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_italian_sentiment","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_italian_sentiment| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.9 MB| + +## References + +https://huggingface.co/pysentimiento/bert-it-sentiment \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_italian_xxl_cased_itacola_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_italian_xxl_cased_itacola_en.md new file mode 100644 index 00000000000000..cc42d85c8ae707 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_italian_xxl_cased_itacola_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_italian_xxl_cased_itacola BertForSequenceClassification from Bainbridge +author: John Snow Labs +name: bert_italian_xxl_cased_itacola +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_italian_xxl_cased_itacola` is a English model originally trained by Bainbridge. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_italian_xxl_cased_itacola_en_5.1.4_3.4_1698208845995.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_italian_xxl_cased_itacola_en_5.1.4_3.4_1698208845995.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_italian_xxl_cased_itacola","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_italian_xxl_cased_itacola","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_italian_xxl_cased_itacola| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.8 MB| + +## References + +https://huggingface.co/Bainbridge/bert-italian-xxl-cased-ItaCoLA \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_arabertv2_finetuned_emotion_3_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_arabertv2_finetuned_emotion_3_en.md new file mode 100644 index 00000000000000..4f5f98e114aa9d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_arabertv2_finetuned_emotion_3_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_arabertv2_finetuned_emotion_3 BertForSequenceClassification from MahaJar +author: John Snow Labs +name: bert_large_arabertv2_finetuned_emotion_3 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_arabertv2_finetuned_emotion_3` is a English model originally trained by MahaJar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_arabertv2_finetuned_emotion_3_en_5.1.4_3.4_1698203316022.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_arabertv2_finetuned_emotion_3_en_5.1.4_3.4_1698203316022.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_arabertv2_finetuned_emotion_3","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_arabertv2_finetuned_emotion_3","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_arabertv2_finetuned_emotion_3| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.4 GB| + +## References + +https://huggingface.co/MahaJar/bert-large-arabertv2-finetuned-emotion_3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_cased_detect_dep_v2_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_cased_detect_dep_v2_en.md new file mode 100644 index 00000000000000..c6626c591bc059 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_cased_detect_dep_v2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_cased_detect_dep_v2 BertForSequenceClassification from Trong-Nghia +author: John Snow Labs +name: bert_large_cased_detect_dep_v2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_cased_detect_dep_v2` is a English model originally trained by Trong-Nghia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_cased_detect_dep_v2_en_5.1.4_3.4_1698199038086.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_cased_detect_dep_v2_en_5.1.4_3.4_1698199038086.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_cased_detect_dep_v2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_cased_detect_dep_v2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_cased_detect_dep_v2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.2 GB| + +## References + +https://huggingface.co/Trong-Nghia/bert-large-cased-detect-dep-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_mnli_3ep_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_mnli_3ep_en.md new file mode 100644 index 00000000000000..4497b08bb6f9f9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_mnli_3ep_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_mnli_3ep BertForSequenceClassification from TehranNLP-org +author: John Snow Labs +name: bert_large_mnli_3ep +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_mnli_3ep` is a English model originally trained by TehranNLP-org. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_mnli_3ep_en_5.1.4_3.4_1698194606103.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_mnli_3ep_en_5.1.4_3.4_1698194606103.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_mnli_3ep","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_mnli_3ep","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_mnli_3ep| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/TehranNLP-org/bert-large-mnli-3ep \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_cola_a_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_cola_a_en.md new file mode 100644 index 00000000000000..5579e40e9d6f6e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_cola_a_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_cola_a BertForSequenceClassification from EhsanAghazadeh +author: John Snow Labs +name: bert_large_uncased_cola_a +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_cola_a` is a English model originally trained by EhsanAghazadeh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_cola_a_en_5.1.4_3.4_1698203702299.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_cola_a_en_5.1.4_3.4_1698203702299.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_cola_a","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_cola_a","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_cola_a| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/EhsanAghazadeh/bert-large-uncased-CoLA_A \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_cola_b_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_cola_b_en.md new file mode 100644 index 00000000000000..4a7a2833858a43 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_cola_b_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_cola_b BertForSequenceClassification from EhsanAghazadeh +author: John Snow Labs +name: bert_large_uncased_cola_b +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_cola_b` is a English model originally trained by EhsanAghazadeh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_cola_b_en_5.1.4_3.4_1698204080875.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_cola_b_en_5.1.4_3.4_1698204080875.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_cola_b","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_cola_b","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_cola_b| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/EhsanAghazadeh/bert-large-uncased-CoLA_B \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_crows_pairs_classifieronly_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_crows_pairs_classifieronly_en.md new file mode 100644 index 00000000000000..8c7f307bd80806 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_crows_pairs_classifieronly_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_crows_pairs_classifieronly BertForSequenceClassification from henryscheible +author: John Snow Labs +name: bert_large_uncased_crows_pairs_classifieronly +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_crows_pairs_classifieronly` is a English model originally trained by henryscheible. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_crows_pairs_classifieronly_en_5.1.4_3.4_1698256326716.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_crows_pairs_classifieronly_en_5.1.4_3.4_1698256326716.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_crows_pairs_classifieronly","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_crows_pairs_classifieronly","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_crows_pairs_classifieronly| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/henryscheible/bert-large-uncased_crows_pairs_classifieronly \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_crows_pairs_finetuned_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_crows_pairs_finetuned_en.md new file mode 100644 index 00000000000000..678438bdcdfdd1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_crows_pairs_finetuned_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_crows_pairs_finetuned BertForSequenceClassification from henryscheible +author: John Snow Labs +name: bert_large_uncased_crows_pairs_finetuned +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_crows_pairs_finetuned` is a English model originally trained by henryscheible. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_crows_pairs_finetuned_en_5.1.4_3.4_1698257524318.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_crows_pairs_finetuned_en_5.1.4_3.4_1698257524318.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_crows_pairs_finetuned","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_crows_pairs_finetuned","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_crows_pairs_finetuned| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/henryscheible/bert-large-uncased_crows_pairs_finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v10_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v10_en.md new file mode 100644 index 00000000000000..ed42d27b7436c6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v10_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_detect_dep_v10 BertForSequenceClassification from Trong-Nghia +author: John Snow Labs +name: bert_large_uncased_detect_dep_v10 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_detect_dep_v10` is a English model originally trained by Trong-Nghia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_detect_dep_v10_en_5.1.4_3.4_1698202953217.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_detect_dep_v10_en_5.1.4_3.4_1698202953217.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_detect_dep_v10","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_detect_dep_v10","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_detect_dep_v10| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Trong-Nghia/bert-large-uncased-detect-dep-v10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v3_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v3_en.md new file mode 100644 index 00000000000000..29ab5c5385bf4b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v3_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_detect_dep_v3 BertForSequenceClassification from Trong-Nghia +author: John Snow Labs +name: bert_large_uncased_detect_dep_v3 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_detect_dep_v3` is a English model originally trained by Trong-Nghia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_detect_dep_v3_en_5.1.4_3.4_1698194887433.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_detect_dep_v3_en_5.1.4_3.4_1698194887433.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_detect_dep_v3","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_detect_dep_v3","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_detect_dep_v3| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Trong-Nghia/bert-large-uncased-detect-dep-v3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v4_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v4_en.md new file mode 100644 index 00000000000000..237f3d7352f6cc --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v4_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_detect_dep_v4 BertForSequenceClassification from Trong-Nghia +author: John Snow Labs +name: bert_large_uncased_detect_dep_v4 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_detect_dep_v4` is a English model originally trained by Trong-Nghia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_detect_dep_v4_en_5.1.4_3.4_1698196092484.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_detect_dep_v4_en_5.1.4_3.4_1698196092484.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_detect_dep_v4","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_detect_dep_v4","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_detect_dep_v4| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Trong-Nghia/bert-large-uncased-detect-dep-v4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v5_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v5_en.md new file mode 100644 index 00000000000000..9f06cfb7e1a675 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v5_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_detect_dep_v5 BertForSequenceClassification from Trong-Nghia +author: John Snow Labs +name: bert_large_uncased_detect_dep_v5 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_detect_dep_v5` is a English model originally trained by Trong-Nghia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_detect_dep_v5_en_5.1.4_3.4_1698197305214.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_detect_dep_v5_en_5.1.4_3.4_1698197305214.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_detect_dep_v5","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_detect_dep_v5","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_detect_dep_v5| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Trong-Nghia/bert-large-uncased-detect-dep-v5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v6_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v6_en.md new file mode 100644 index 00000000000000..2152a2072767a2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v6_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_detect_dep_v6 BertForSequenceClassification from Trong-Nghia +author: John Snow Labs +name: bert_large_uncased_detect_dep_v6 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_detect_dep_v6` is a English model originally trained by Trong-Nghia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_detect_dep_v6_en_5.1.4_3.4_1698197844718.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_detect_dep_v6_en_5.1.4_3.4_1698197844718.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_detect_dep_v6","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_detect_dep_v6","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_detect_dep_v6| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Trong-Nghia/bert-large-uncased-detect-dep-v6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v7_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v7_en.md new file mode 100644 index 00000000000000..67b9f8352d4544 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v7_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_detect_dep_v7 BertForSequenceClassification from Trong-Nghia +author: John Snow Labs +name: bert_large_uncased_detect_dep_v7 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_detect_dep_v7` is a English model originally trained by Trong-Nghia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_detect_dep_v7_en_5.1.4_3.4_1698199359811.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_detect_dep_v7_en_5.1.4_3.4_1698199359811.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_detect_dep_v7","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_detect_dep_v7","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_detect_dep_v7| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Trong-Nghia/bert-large-uncased-detect-dep-v7 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v8_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v8_en.md new file mode 100644 index 00000000000000..0aa14af21905ca --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_detect_dep_v8 BertForSequenceClassification from Trong-Nghia +author: John Snow Labs +name: bert_large_uncased_detect_dep_v8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_detect_dep_v8` is a English model originally trained by Trong-Nghia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_detect_dep_v8_en_5.1.4_3.4_1698200112307.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_detect_dep_v8_en_5.1.4_3.4_1698200112307.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_detect_dep_v8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_detect_dep_v8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_detect_dep_v8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Trong-Nghia/bert-large-uncased-detect-dep-v8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v9_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v9_en.md new file mode 100644 index 00000000000000..248307e5797d98 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_dep_v9_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_detect_dep_v9 BertForSequenceClassification from Trong-Nghia +author: John Snow Labs +name: bert_large_uncased_detect_dep_v9 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_detect_dep_v9` is a English model originally trained by Trong-Nghia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_detect_dep_v9_en_5.1.4_3.4_1698200994577.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_detect_dep_v9_en_5.1.4_3.4_1698200994577.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_detect_dep_v9","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_detect_dep_v9","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_detect_dep_v9| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Trong-Nghia/bert-large-uncased-detect-dep-v9 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_depression_stage_one_v3_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_depression_stage_one_v3_en.md new file mode 100644 index 00000000000000..fa3e4d62cf706c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_depression_stage_one_v3_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_detect_depression_stage_one_v3 BertForSequenceClassification from hoanghoavienvo +author: John Snow Labs +name: bert_large_uncased_detect_depression_stage_one_v3 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_detect_depression_stage_one_v3` is a English model originally trained by hoanghoavienvo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_detect_depression_stage_one_v3_en_5.1.4_3.4_1698192511564.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_detect_depression_stage_one_v3_en_5.1.4_3.4_1698192511564.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_detect_depression_stage_one_v3","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_detect_depression_stage_one_v3","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_detect_depression_stage_one_v3| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/hoanghoavienvo/bert-large-uncased-detect-depression-stage-one-v3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_depression_stage_one_v4_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_depression_stage_one_v4_en.md new file mode 100644 index 00000000000000..261fa9a94f8570 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_detect_depression_stage_one_v4_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_detect_depression_stage_one_v4 BertForSequenceClassification from hoanghoavienvo +author: John Snow Labs +name: bert_large_uncased_detect_depression_stage_one_v4 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_detect_depression_stage_one_v4` is a English model originally trained by hoanghoavienvo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_detect_depression_stage_one_v4_en_5.1.4_3.4_1698193240825.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_detect_depression_stage_one_v4_en_5.1.4_3.4_1698193240825.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_detect_depression_stage_one_v4","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_detect_depression_stage_one_v4","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_detect_depression_stage_one_v4| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/hoanghoavienvo/bert-large-uncased-detect-depression-stage-one-v4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_hoax_classifier_v1_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_hoax_classifier_v1_en.md new file mode 100644 index 00000000000000..d70f7e5053f647 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_hoax_classifier_v1_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_hoax_classifier_v1 BertForSequenceClassification from research-dump +author: John Snow Labs +name: bert_large_uncased_hoax_classifier_v1 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_hoax_classifier_v1` is a English model originally trained by research-dump. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_hoax_classifier_v1_en_5.1.4_3.4_1698229551553.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_hoax_classifier_v1_en_5.1.4_3.4_1698229551553.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_hoax_classifier_v1","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_hoax_classifier_v1","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_hoax_classifier_v1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/research-dump/bert-large-uncased_hoax_classifier_v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_mnli_ofirzaf_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_mnli_ofirzaf_en.md new file mode 100644 index 00000000000000..63886fb14ffb4e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_mnli_ofirzaf_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_mnli_ofirzaf BertForSequenceClassification from ofirzaf +author: John Snow Labs +name: bert_large_uncased_mnli_ofirzaf +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_mnli_ofirzaf` is a English model originally trained by ofirzaf. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_mnli_ofirzaf_en_5.1.4_3.4_1698239030775.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_mnli_ofirzaf_en_5.1.4_3.4_1698239030775.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_mnli_ofirzaf","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_mnli_ofirzaf","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_mnli_ofirzaf| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/ofirzaf/bert-large-uncased-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_16_13_30_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_16_13_30_en.md new file mode 100644 index 00000000000000..0f548ac7d8a7ca --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_16_13_30_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_sst_2_16_13_30 BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_large_uncased_sst_2_16_13_30 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_sst_2_16_13_30` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_sst_2_16_13_30_en_5.1.4_3.4_1698224647052.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_sst_2_16_13_30_en_5.1.4_3.4_1698224647052.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_sst_2_16_13_30","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_sst_2_16_13_30","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_sst_2_16_13_30| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/simonycl/bert-large-uncased-sst-2-16-13-30 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_16_13_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_16_13_en.md new file mode 100644 index 00000000000000..42aebe39703aa9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_16_13_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_sst_2_16_13 BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_large_uncased_sst_2_16_13 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_sst_2_16_13` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_sst_2_16_13_en_5.1.4_3.4_1698213051929.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_sst_2_16_13_en_5.1.4_3.4_1698213051929.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_sst_2_16_13","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_sst_2_16_13","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_sst_2_16_13| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/simonycl/bert-large-uncased-sst-2-16-13 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_16_13_smoothed_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_16_13_smoothed_en.md new file mode 100644 index 00000000000000..3f4e8dd0f028f6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_16_13_smoothed_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_sst_2_16_13_smoothed BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_large_uncased_sst_2_16_13_smoothed +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_sst_2_16_13_smoothed` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_sst_2_16_13_smoothed_en_5.1.4_3.4_1698220491868.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_sst_2_16_13_smoothed_en_5.1.4_3.4_1698220491868.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_sst_2_16_13_smoothed","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_sst_2_16_13_smoothed","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_sst_2_16_13_smoothed| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/simonycl/bert-large-uncased-sst-2-16-13-smoothed \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_32_13_30_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_32_13_30_en.md new file mode 100644 index 00000000000000..10834a73e981af --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_32_13_30_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_sst_2_32_13_30 BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_large_uncased_sst_2_32_13_30 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_sst_2_32_13_30` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_sst_2_32_13_30_en_5.1.4_3.4_1698225008323.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_sst_2_32_13_30_en_5.1.4_3.4_1698225008323.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_sst_2_32_13_30","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_sst_2_32_13_30","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_sst_2_32_13_30| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/simonycl/bert-large-uncased-sst-2-32-13-30 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_32_13_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_32_13_en.md new file mode 100644 index 00000000000000..ddab8271fd3644 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_32_13_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_sst_2_32_13 BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_large_uncased_sst_2_32_13 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_sst_2_32_13` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_sst_2_32_13_en_5.1.4_3.4_1698213363304.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_sst_2_32_13_en_5.1.4_3.4_1698213363304.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_sst_2_32_13","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_sst_2_32_13","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_sst_2_32_13| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/simonycl/bert-large-uncased-sst-2-32-13 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_32_13_smoothed_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_32_13_smoothed_en.md new file mode 100644 index 00000000000000..01a6edabf1813d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_32_13_smoothed_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_sst_2_32_13_smoothed BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_large_uncased_sst_2_32_13_smoothed +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_sst_2_32_13_smoothed` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_sst_2_32_13_smoothed_en_5.1.4_3.4_1698215795624.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_sst_2_32_13_smoothed_en_5.1.4_3.4_1698215795624.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_sst_2_32_13_smoothed","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_sst_2_32_13_smoothed","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_sst_2_32_13_smoothed| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/simonycl/bert-large-uncased-sst-2-32-13-smoothed \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_64_13_30_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_64_13_30_en.md new file mode 100644 index 00000000000000..7647d4ca3a2aab --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_64_13_30_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_sst_2_64_13_30 BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_large_uncased_sst_2_64_13_30 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_sst_2_64_13_30` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_sst_2_64_13_30_en_5.1.4_3.4_1698226238586.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_sst_2_64_13_30_en_5.1.4_3.4_1698226238586.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_sst_2_64_13_30","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_sst_2_64_13_30","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_sst_2_64_13_30| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/simonycl/bert-large-uncased-sst-2-64-13-30 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_64_13_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_64_13_en.md new file mode 100644 index 00000000000000..1d1bd3cc2072b8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_64_13_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_sst_2_64_13 BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_large_uncased_sst_2_64_13 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_sst_2_64_13` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_sst_2_64_13_en_5.1.4_3.4_1698213724985.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_sst_2_64_13_en_5.1.4_3.4_1698213724985.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_sst_2_64_13","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_sst_2_64_13","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_sst_2_64_13| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/simonycl/bert-large-uncased-sst-2-64-13 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_64_13_smoothed_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_64_13_smoothed_en.md new file mode 100644 index 00000000000000..049a4b9154e80a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_sst_2_64_13_smoothed_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_sst_2_64_13_smoothed BertForSequenceClassification from simonycl +author: John Snow Labs +name: bert_large_uncased_sst_2_64_13_smoothed +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_sst_2_64_13_smoothed` is a English model originally trained by simonycl. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_sst_2_64_13_smoothed_en_5.1.4_3.4_1698216168271.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_sst_2_64_13_smoothed_en_5.1.4_3.4_1698216168271.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_sst_2_64_13_smoothed","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_sst_2_64_13_smoothed","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_sst_2_64_13_smoothed| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/simonycl/bert-large-uncased-sst-2-64-13-smoothed \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_stereoset_classifieronly_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_stereoset_classifieronly_en.md new file mode 100644 index 00000000000000..8db133d915d1f0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_stereoset_classifieronly_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_stereoset_classifieronly BertForSequenceClassification from henryscheible +author: John Snow Labs +name: bert_large_uncased_stereoset_classifieronly +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_stereoset_classifieronly` is a English model originally trained by henryscheible. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_stereoset_classifieronly_en_5.1.4_3.4_1698258967203.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_stereoset_classifieronly_en_5.1.4_3.4_1698258967203.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_stereoset_classifieronly","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_stereoset_classifieronly","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_stereoset_classifieronly| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/henryscheible/bert-large-uncased_stereoset_classifieronly \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_stereoset_finetuned_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_stereoset_finetuned_en.md new file mode 100644 index 00000000000000..d9eaef2a8af3bf --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_stereoset_finetuned_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_stereoset_finetuned BertForSequenceClassification from henryscheible +author: John Snow Labs +name: bert_large_uncased_stereoset_finetuned +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_stereoset_finetuned` is a English model originally trained by henryscheible. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_stereoset_finetuned_en_5.1.4_3.4_1698200996741.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_stereoset_finetuned_en_5.1.4_3.4_1698200996741.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_stereoset_finetuned","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_stereoset_finetuned","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_stereoset_finetuned| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/henryscheible/bert-large-uncased_stereoset_finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_polifact_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_polifact_en.md new file mode 100644 index 00000000000000..400050e606034d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_polifact_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_polifact BertForSequenceClassification from anuj55 +author: John Snow Labs +name: bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_polifact +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_polifact` is a English model originally trained by anuj55. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_polifact_en_5.1.4_3.4_1698272933947.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_polifact_en_5.1.4_3.4_1698272933947.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_polifact","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_polifact","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_whole_word_masking_finetuned_squad_finetuned_polifact| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/anuj55/bert-large-uncased-whole-word-masking-finetuned-squad-finetuned-polifact \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_winobias_classifieronly_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_winobias_classifieronly_en.md new file mode 100644 index 00000000000000..1e22f3de8c730e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_winobias_classifieronly_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_winobias_classifieronly BertForSequenceClassification from henryscheible +author: John Snow Labs +name: bert_large_uncased_winobias_classifieronly +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_winobias_classifieronly` is a English model originally trained by henryscheible. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_winobias_classifieronly_en_5.1.4_3.4_1698261699082.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_winobias_classifieronly_en_5.1.4_3.4_1698261699082.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_winobias_classifieronly","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_winobias_classifieronly","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_winobias_classifieronly| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/henryscheible/bert-large-uncased_winobias_classifieronly \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_winobias_finetuned_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_winobias_finetuned_en.md new file mode 100644 index 00000000000000..e7cc50de66b3e2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_winobias_finetuned_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_winobias_finetuned BertForSequenceClassification from henryscheible +author: John Snow Labs +name: bert_large_uncased_winobias_finetuned +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_winobias_finetuned` is a English model originally trained by henryscheible. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_winobias_finetuned_en_5.1.4_3.4_1698260379138.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_winobias_finetuned_en_5.1.4_3.4_1698260379138.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_winobias_finetuned","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_winobias_finetuned","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_winobias_finetuned| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/henryscheible/bert-large-uncased_winobias_finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_with_preprocess_finetuned_emotion_5_epochs_5e_05_lr_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_with_preprocess_finetuned_emotion_5_epochs_5e_05_lr_en.md new file mode 100644 index 00000000000000..0979b32d51dfe9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_large_uncased_with_preprocess_finetuned_emotion_5_epochs_5e_05_lr_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_with_preprocess_finetuned_emotion_5_epochs_5e_05_lr BertForSequenceClassification from Ioanaaaaaaa +author: John Snow Labs +name: bert_large_uncased_with_preprocess_finetuned_emotion_5_epochs_5e_05_lr +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_with_preprocess_finetuned_emotion_5_epochs_5e_05_lr` is a English model originally trained by Ioanaaaaaaa. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_with_preprocess_finetuned_emotion_5_epochs_5e_05_lr_en_5.1.4_3.4_1698194379064.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_with_preprocess_finetuned_emotion_5_epochs_5e_05_lr_en_5.1.4_3.4_1698194379064.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_with_preprocess_finetuned_emotion_5_epochs_5e_05_lr","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_with_preprocess_finetuned_emotion_5_epochs_5e_05_lr","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_with_preprocess_finetuned_emotion_5_epochs_5e_05_lr| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Ioanaaaaaaa/bert-large-uncased-with-preprocess-finetuned-emotion-5-epochs-5e-05-lr \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_lf_bond_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_lf_bond_en.md new file mode 100644 index 00000000000000..514f68cabbf9e2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_lf_bond_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_lf_bond BertForSequenceClassification from himanshubeniwal +author: John Snow Labs +name: bert_lf_bond +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_lf_bond` is a English model originally trained by himanshubeniwal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_lf_bond_en_5.1.4_3.4_1698213000387.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_lf_bond_en_5.1.4_3.4_1698213000387.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_lf_bond","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_lf_bond","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_lf_bond| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/himanshubeniwal/bert_lf_bond \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_lf_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_lf_en.md new file mode 100644 index 00000000000000..80d99f1f49cc92 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_lf_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_lf BertForSequenceClassification from himanshubeniwal +author: John Snow Labs +name: bert_lf +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_lf` is a English model originally trained by himanshubeniwal. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_lf_en_5.1.4_3.4_1698209907388.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_lf_en_5.1.4_3.4_1698209907388.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_lf","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_lf","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_lf| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/himanshubeniwal/bert_lf \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_mini_finetuned_mnli_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_mini_finetuned_mnli_en.md new file mode 100644 index 00000000000000..c86eb14f202c19 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_mini_finetuned_mnli_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_mini_finetuned_mnli BertForSequenceClassification from M-FAC +author: John Snow Labs +name: bert_mini_finetuned_mnli +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_mini_finetuned_mnli` is a English model originally trained by M-FAC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_mini_finetuned_mnli_en_5.1.4_3.4_1698222045987.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_mini_finetuned_mnli_en_5.1.4_3.4_1698222045987.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_mini_finetuned_mnli","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_mini_finetuned_mnli","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_mini_finetuned_mnli| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|42.1 MB| + +## References + +https://huggingface.co/M-FAC/bert-mini-finetuned-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_mini_finetuned_mrpc_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_mini_finetuned_mrpc_en.md new file mode 100644 index 00000000000000..4d6737a21da254 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_mini_finetuned_mrpc_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_mini_finetuned_mrpc BertForSequenceClassification from M-FAC +author: John Snow Labs +name: bert_mini_finetuned_mrpc +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_mini_finetuned_mrpc` is a English model originally trained by M-FAC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_mini_finetuned_mrpc_en_5.1.4_3.4_1698222142012.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_mini_finetuned_mrpc_en_5.1.4_3.4_1698222142012.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_mini_finetuned_mrpc","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_mini_finetuned_mrpc","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_mini_finetuned_mrpc| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|42.1 MB| + +## References + +https://huggingface.co/M-FAC/bert-mini-finetuned-mrpc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_mini_finetuned_qnli_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_mini_finetuned_qnli_en.md new file mode 100644 index 00000000000000..06edc3f29f8485 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_mini_finetuned_qnli_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_mini_finetuned_qnli BertForSequenceClassification from M-FAC +author: John Snow Labs +name: bert_mini_finetuned_qnli +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_mini_finetuned_qnli` is a English model originally trained by M-FAC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_mini_finetuned_qnli_en_5.1.4_3.4_1698222259511.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_mini_finetuned_qnli_en_5.1.4_3.4_1698222259511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_mini_finetuned_qnli","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_mini_finetuned_qnli","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_mini_finetuned_qnli| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|42.1 MB| + +## References + +https://huggingface.co/M-FAC/bert-mini-finetuned-qnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_mini_finetuned_qqp_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_mini_finetuned_qqp_en.md new file mode 100644 index 00000000000000..7dc7272d8455d0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_mini_finetuned_qqp_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_mini_finetuned_qqp BertForSequenceClassification from M-FAC +author: John Snow Labs +name: bert_mini_finetuned_qqp +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_mini_finetuned_qqp` is a English model originally trained by M-FAC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_mini_finetuned_qqp_en_5.1.4_3.4_1698222353761.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_mini_finetuned_qqp_en_5.1.4_3.4_1698222353761.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_mini_finetuned_qqp","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_mini_finetuned_qqp","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_mini_finetuned_qqp| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|42.1 MB| + +## References + +https://huggingface.co/M-FAC/bert-mini-finetuned-qqp \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_mini_finetuned_sst2_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_mini_finetuned_sst2_en.md new file mode 100644 index 00000000000000..5647461caea8d4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_mini_finetuned_sst2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_mini_finetuned_sst2 BertForSequenceClassification from M-FAC +author: John Snow Labs +name: bert_mini_finetuned_sst2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_mini_finetuned_sst2` is a English model originally trained by M-FAC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_mini_finetuned_sst2_en_5.1.4_3.4_1698222448691.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_mini_finetuned_sst2_en_5.1.4_3.4_1698222448691.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_mini_finetuned_sst2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_mini_finetuned_sst2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_mini_finetuned_sst2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|42.1 MB| + +## References + +https://huggingface.co/M-FAC/bert-mini-finetuned-sst2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_mini_finetuned_stsb_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_mini_finetuned_stsb_en.md new file mode 100644 index 00000000000000..34b3b2d4bac057 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_mini_finetuned_stsb_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_mini_finetuned_stsb BertForSequenceClassification from M-FAC +author: John Snow Labs +name: bert_mini_finetuned_stsb +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_mini_finetuned_stsb` is a English model originally trained by M-FAC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_mini_finetuned_stsb_en_5.1.4_3.4_1698222538855.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_mini_finetuned_stsb_en_5.1.4_3.4_1698222538855.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_mini_finetuned_stsb","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_mini_finetuned_stsb","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_mini_finetuned_stsb| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|42.1 MB| + +## References + +https://huggingface.co/M-FAC/bert-mini-finetuned-stsb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_mixed_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_mixed_en.md new file mode 100644 index 00000000000000..49aa9d877edc14 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_mixed_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_mixed BertForSequenceClassification from PravallikaMyneni +author: John Snow Labs +name: bert_mixed +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_mixed` is a English model originally trained by PravallikaMyneni. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_mixed_en_5.1.4_3.4_1698222545171.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_mixed_en_5.1.4_3.4_1698222545171.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_mixed","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_mixed","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_mixed| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/PravallikaMyneni/bert_mixed \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_multilingual_go_emtions_xx.md b/docs/_posts/ahmedlone127/2023-10-25-bert_multilingual_go_emtions_xx.md new file mode 100644 index 00000000000000..d4bad723fd20dd --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_multilingual_go_emtions_xx.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Multilingual bert_multilingual_go_emtions BertForSequenceClassification from SchuylerH +author: John Snow Labs +name: bert_multilingual_go_emtions +date: 2023-10-25 +tags: [bert, xx, open_source, sequence_classification, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_multilingual_go_emtions` is a Multilingual model originally trained by SchuylerH. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_multilingual_go_emtions_xx_5.1.4_3.4_1698200634121.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_multilingual_go_emtions_xx_5.1.4_3.4_1698200634121.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_multilingual_go_emtions","xx")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_multilingual_go_emtions","xx") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_multilingual_go_emtions| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/SchuylerH/bert-multilingual-go-emtions \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_multilingual_sentiment_xx.md b/docs/_posts/ahmedlone127/2023-10-25-bert_multilingual_sentiment_xx.md new file mode 100644 index 00000000000000..06334346e1aa5f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_multilingual_sentiment_xx.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Multilingual bert_multilingual_sentiment BertForSequenceClassification from marianna13 +author: John Snow Labs +name: bert_multilingual_sentiment +date: 2023-10-25 +tags: [bert, xx, open_source, sequence_classification, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_multilingual_sentiment` is a Multilingual model originally trained by marianna13. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_multilingual_sentiment_xx_5.1.4_3.4_1698214796118.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_multilingual_sentiment_xx_5.1.4_3.4_1698214796118.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_multilingual_sentiment","xx")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_multilingual_sentiment","xx") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_multilingual_sentiment| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|627.7 MB| + +## References + +https://huggingface.co/marianna13/bert-multilingual-sentiment \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_multilingual_xx.md b/docs/_posts/ahmedlone127/2023-10-25-bert_multilingual_xx.md new file mode 100644 index 00000000000000..673fa29afa83d0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_multilingual_xx.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Multilingual bert_multilingual BertForSequenceClassification from jiiyy +author: John Snow Labs +name: bert_multilingual +date: 2023-10-25 +tags: [bert, xx, open_source, sequence_classification, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_multilingual` is a Multilingual model originally trained by jiiyy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_multilingual_xx_5.1.4_3.4_1698258613797.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_multilingual_xx_5.1.4_3.4_1698258613797.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_multilingual","xx")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_multilingual","xx") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_multilingual| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/jiiyy/bert_multilingual \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_pre_doc_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_pre_doc_en.md new file mode 100644 index 00000000000000..75e5c6f1d1b618 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_pre_doc_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_pre_doc BertForSequenceClassification from LilaBoualili +author: John Snow Labs +name: bert_pre_doc +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_pre_doc` is a English model originally trained by LilaBoualili. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_pre_doc_en_5.1.4_3.4_1698220828401.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_pre_doc_en_5.1.4_3.4_1698220828401.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_pre_doc","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_pre_doc","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_pre_doc| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/LilaBoualili/bert-pre-doc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_pre_pair_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_pre_pair_en.md new file mode 100644 index 00000000000000..8c09fb2a1ae7e0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_pre_pair_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_pre_pair BertForSequenceClassification from LilaBoualili +author: John Snow Labs +name: bert_pre_pair +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_pre_pair` is a English model originally trained by LilaBoualili. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_pre_pair_en_5.1.4_3.4_1698221017879.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_pre_pair_en_5.1.4_3.4_1698221017879.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_pre_pair","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_pre_pair","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_pre_pair| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/LilaBoualili/bert-pre-pair \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_regression_dynamic_tokenlimit_v1_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_regression_dynamic_tokenlimit_v1_en.md new file mode 100644 index 00000000000000..24d3d546df2032 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_regression_dynamic_tokenlimit_v1_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_regression_dynamic_tokenlimit_v1 BertForSequenceClassification from OZ1150 +author: John Snow Labs +name: bert_regression_dynamic_tokenlimit_v1 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_regression_dynamic_tokenlimit_v1` is a English model originally trained by OZ1150. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_regression_dynamic_tokenlimit_v1_en_5.1.4_3.4_1698205343608.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_regression_dynamic_tokenlimit_v1_en_5.1.4_3.4_1698205343608.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_regression_dynamic_tokenlimit_v1","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_regression_dynamic_tokenlimit_v1","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_regression_dynamic_tokenlimit_v1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/OZ1150/bert-regression-dynamic-tokenlimit-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_sdg_french_fr.md b/docs/_posts/ahmedlone127/2023-10-25-bert_sdg_french_fr.md new file mode 100644 index 00000000000000..ada1dbaeb13105 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_sdg_french_fr.md @@ -0,0 +1,97 @@ +--- +layout: model +title: French bert_sdg_french BertForSequenceClassification from ilovebots +author: John Snow Labs +name: bert_sdg_french +date: 2023-10-25 +tags: [bert, fr, open_source, sequence_classification, onnx] +task: Text Classification +language: fr +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sdg_french` is a French model originally trained by ilovebots. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sdg_french_fr_5.1.4_3.4_1698214647394.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sdg_french_fr_5.1.4_3.4_1698214647394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sdg_french","fr")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sdg_french","fr") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sdg_french| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|fr| +|Size:|414.6 MB| + +## References + +https://huggingface.co/ilovebots/bert-sdg-french \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_sentence_classifier_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_sentence_classifier_en.md new file mode 100644 index 00000000000000..611b1a83e0f076 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_sentence_classifier_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_sentence_classifier BertForSequenceClassification from Paleontolog +author: John Snow Labs +name: bert_sentence_classifier +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sentence_classifier` is a English model originally trained by Paleontolog. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sentence_classifier_en_5.1.4_3.4_1698242352864.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sentence_classifier_en_5.1.4_3.4_1698242352864.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sentence_classifier","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sentence_classifier","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sentence_classifier| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|667.3 MB| + +## References + +https://huggingface.co/Paleontolog/bert_sentence_classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_sequce_classifier_paraphrase_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_sequce_classifier_paraphrase_en.md new file mode 100644 index 00000000000000..01140afc54eaa6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_sequce_classifier_paraphrase_en.md @@ -0,0 +1,100 @@ +--- +layout: model +title: English BertForSequenceClassification Cased model (from Prompsit) +author: John Snow Labs +name: bert_sequce_classifier_paraphrase +date: 2023-10-25 +tags: [en, open_source, bert, sequence_classification, ner, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `paraphrase-bert-en` is a English model originally trained by `Prompsit`. + +## Predicted Entities + +`Not Paraphrase`, `Paraphrase` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequce_classifier_paraphrase_en_5.1.4_3.4_1698231258424.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequce_classifier_paraphrase_en_5.1.4_3.4_1698231258424.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequce_classifier_paraphrase","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequce_classifier_paraphrase","en") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequce_classifier_paraphrase| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|409.4 MB| +|Case sensitive:|true| +|Max sentence length:|128| + +## References + +References + +- https://huggingface.co/Prompsit/paraphrase-bert-en \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_base_uncased_finetuned_surveyclassification_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_base_uncased_finetuned_surveyclassification_en.md new file mode 100644 index 00000000000000..49d58adbd7092c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_base_uncased_finetuned_surveyclassification_en.md @@ -0,0 +1,100 @@ +--- +layout: model +title: English BertForSequenceClassification Base Uncased model (from Jorgeutd) +author: John Snow Labs +name: bert_sequence_classifier_base_uncased_finetuned_surveyclassification +date: 2023-10-25 +tags: [en, open_source, bert, sequence_classification, ner, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-uncased-finetuned-surveyclassification` is a English model originally trained by `Jorgeutd`. + +## Predicted Entities + +`positive`, `neutral`, `negative` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_uncased_finetuned_surveyclassification_en_5.1.4_3.4_1698219648617.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_uncased_finetuned_surveyclassification_en_5.1.4_3.4_1698219648617.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_uncased_finetuned_surveyclassification","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_uncased_finetuned_surveyclassification","en") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_base_uncased_finetuned_surveyclassification| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|409.4 MB| +|Case sensitive:|true| +|Max sentence length:|128| + +## References + +References + +- https://huggingface.co/Jorgeutd/bert-base-uncased-finetuned-surveyclassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_base_uncased_sst2_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_base_uncased_sst2_en.md new file mode 100644 index 00000000000000..bf377d771b78ab --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_base_uncased_sst2_en.md @@ -0,0 +1,101 @@ +--- +layout: model +title: English BertForSequenceClassification Base Uncased model (from JeremiahZ) +author: John Snow Labs +name: bert_sequence_classifier_base_uncased_sst2 +date: 2023-10-25 +tags: [en, open_source, bert, sequence_classification, ner, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-uncased-sst2` is a English model originally trained by `JeremiahZ`. + +## Predicted Entities + +`positive`, `negative` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_uncased_sst2_en_5.1.4_3.4_1698208956258.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_base_uncased_sst2_en_5.1.4_3.4_1698208956258.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_uncased_sst2","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_base_uncased_sst2","en") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_base_uncased_sst2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|409.4 MB| +|Case sensitive:|true| +|Max sentence length:|128| + +## References + +References + +- https://huggingface.co/JeremiahZ/bert-base-uncased-sst2 +- https://paperswithcode.com/sota?task=Text+Classification&dataset=GLUE+SST2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_arabic_ar.md b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_arabic_ar.md new file mode 100644 index 00000000000000..69961195e6eb56 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_arabic_ar.md @@ -0,0 +1,102 @@ +--- +layout: model +title: Arabic BertForSequenceClassification Cased model (from Hate-speech-CNERG) +author: John Snow Labs +name: bert_sequence_classifier_dehate_mono_arabic +date: 2023-10-25 +tags: [ar, open_source, bert, sequence_classification, ner, onnx] +task: Named Entity Recognition +language: ar +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `dehatebert-mono-arabic` is a Arabic model originally trained by `Hate-speech-CNERG`. + +## Predicted Entities + +`NON_HATE`, `HATE` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_dehate_mono_arabic_ar_5.1.4_3.4_1698205916789.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_dehate_mono_arabic_ar_5.1.4_3.4_1698205916789.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_dehate_mono_arabic","ar") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_dehate_mono_arabic","ar") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_dehate_mono_arabic| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|ar| +|Size:|627.7 MB| +|Case sensitive:|true| +|Max sentence length:|128| + +## References + +References + +- https://huggingface.co/Hate-speech-CNERG/dehatebert-mono-arabic +- https://github.com/punyajoy/DE-LIMIT +- https://arxiv.org/abs/2004.06465 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_english_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_english_en.md new file mode 100644 index 00000000000000..913670c6ea41f1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_english_en.md @@ -0,0 +1,102 @@ +--- +layout: model +title: English BertForSequenceClassification Cased model (from Hate-speech-CNERG) +author: John Snow Labs +name: bert_sequence_classifier_dehate_mono_english +date: 2023-10-25 +tags: [en, open_source, bert, sequence_classification, ner, onnx] +task: Named Entity Recognition +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `dehatebert-mono-english` is a English model originally trained by `Hate-speech-CNERG`. + +## Predicted Entities + +`NON_HATE`, `HATE` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_dehate_mono_english_en_5.1.4_3.4_1698206347763.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_dehate_mono_english_en_5.1.4_3.4_1698206347763.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_dehate_mono_english","en") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_dehate_mono_english","en") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_dehate_mono_english| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|en| +|Size:|627.7 MB| +|Case sensitive:|true| +|Max sentence length:|128| + +## References + +References + +- https://huggingface.co/Hate-speech-CNERG/dehatebert-mono-english +- https://github.com/punyajoy/DE-LIMIT +- https://arxiv.org/abs/2004.06465 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_french_fr.md b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_french_fr.md new file mode 100644 index 00000000000000..ca3f72e0baf34a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_french_fr.md @@ -0,0 +1,102 @@ +--- +layout: model +title: French BertForSequenceClassification Cased model (from Hate-speech-CNERG) +author: John Snow Labs +name: bert_sequence_classifier_dehate_mono_french +date: 2023-10-25 +tags: [fr, open_source, bert, sequence_classification, ner, onnx] +task: Named Entity Recognition +language: fr +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `dehatebert-mono-french` is a French model originally trained by `Hate-speech-CNERG`. + +## Predicted Entities + +`NON_HATE`, `HATE` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_dehate_mono_french_fr_5.1.4_3.4_1698206729043.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_dehate_mono_french_fr_5.1.4_3.4_1698206729043.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_dehate_mono_french","fr") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_dehate_mono_french","fr") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_dehate_mono_french| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|fr| +|Size:|627.7 MB| +|Case sensitive:|true| +|Max sentence length:|128| + +## References + +References + +- https://huggingface.co/Hate-speech-CNERG/dehatebert-mono-french +- https://github.com/punyajoy/DE-LIMIT +- https://arxiv.org/abs/2004.06465 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_german_de.md b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_german_de.md new file mode 100644 index 00000000000000..a1e3014e6faea9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_german_de.md @@ -0,0 +1,102 @@ +--- +layout: model +title: German BertForSequenceClassification Cased model (from Hate-speech-CNERG) +author: John Snow Labs +name: bert_sequence_classifier_dehate_mono_german +date: 2023-10-25 +tags: [de, open_source, bert, sequence_classification, ner, onnx] +task: Named Entity Recognition +language: de +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `dehatebert-mono-german` is a German model originally trained by `Hate-speech-CNERG`. + +## Predicted Entities + +`NON_HATE`, `HATE` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_dehate_mono_german_de_5.1.4_3.4_1698207128997.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_dehate_mono_german_de_5.1.4_3.4_1698207128997.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_dehate_mono_german","de") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_dehate_mono_german","de") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_dehate_mono_german| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|de| +|Size:|627.7 MB| +|Case sensitive:|true| +|Max sentence length:|128| + +## References + +References + +- https://huggingface.co/Hate-speech-CNERG/dehatebert-mono-german +- https://github.com/punyajoy/DE-LIMIT +- https://arxiv.org/abs/2004.06465 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_italian_it.md b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_italian_it.md new file mode 100644 index 00000000000000..2f54f547c7aacb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_italian_it.md @@ -0,0 +1,102 @@ +--- +layout: model +title: Italian BertForSequenceClassification Cased model (from Hate-speech-CNERG) +author: John Snow Labs +name: bert_sequence_classifier_dehate_mono_italian +date: 2023-10-25 +tags: [it, open_source, bert, sequence_classification, ner, onnx] +task: Named Entity Recognition +language: it +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `dehatebert-mono-italian` is a Italian model originally trained by `Hate-speech-CNERG`. + +## Predicted Entities + +`NON_HATE`, `HATE` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_dehate_mono_italian_it_5.1.4_3.4_1698207923030.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_dehate_mono_italian_it_5.1.4_3.4_1698207923030.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_dehate_mono_italian","it") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_dehate_mono_italian","it") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_dehate_mono_italian| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|it| +|Size:|627.7 MB| +|Case sensitive:|true| +|Max sentence length:|128| + +## References + +References + +- https://huggingface.co/Hate-speech-CNERG/dehatebert-mono-italian +- https://github.com/punyajoy/DE-LIMIT +- https://arxiv.org/abs/2004.06465 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_polish_pl.md b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_polish_pl.md new file mode 100644 index 00000000000000..b06094f1d113da --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_polish_pl.md @@ -0,0 +1,102 @@ +--- +layout: model +title: Polish BertForSequenceClassification Cased model (from Hate-speech-CNERG) +author: John Snow Labs +name: bert_sequence_classifier_dehate_mono_polish +date: 2023-10-25 +tags: [pl, open_source, bert, sequence_classification, ner, onnx] +task: Named Entity Recognition +language: pl +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `dehatebert-mono-polish` is a Polish model originally trained by `Hate-speech-CNERG`. + +## Predicted Entities + +`NON_HATE`, `HATE` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_dehate_mono_polish_pl_5.1.4_3.4_1698208354124.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_dehate_mono_polish_pl_5.1.4_3.4_1698208354124.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_dehate_mono_polish","pl") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_dehate_mono_polish","pl") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_dehate_mono_polish| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|pl| +|Size:|627.7 MB| +|Case sensitive:|true| +|Max sentence length:|128| + +## References + +References + +- https://huggingface.co/Hate-speech-CNERG/dehatebert-mono-polish +- https://github.com/punyajoy/DE-LIMIT +- https://arxiv.org/abs/2004.06465 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_portugese_pt.md b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_portugese_pt.md new file mode 100644 index 00000000000000..5d054e173420dd --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_portugese_pt.md @@ -0,0 +1,102 @@ +--- +layout: model +title: Portuguese BertForSequenceClassification Cased model (from Hate-speech-CNERG) +author: John Snow Labs +name: bert_sequence_classifier_dehate_mono_portugese +date: 2023-10-25 +tags: [pt, open_source, bert, sequence_classification, ner, onnx] +task: Named Entity Recognition +language: pt +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `dehatebert-mono-portugese` is a Portuguese model originally trained by `Hate-speech-CNERG`. + +## Predicted Entities + +`NON_HATE`, `HATE` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_dehate_mono_portugese_pt_5.1.4_3.4_1698208710232.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_dehate_mono_portugese_pt_5.1.4_3.4_1698208710232.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_dehate_mono_portugese","pt") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_dehate_mono_portugese","pt") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_dehate_mono_portugese| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|pt| +|Size:|627.7 MB| +|Case sensitive:|true| +|Max sentence length:|128| + +## References + +References + +- https://huggingface.co/Hate-speech-CNERG/dehatebert-mono-portugese +- https://github.com/punyajoy/DE-LIMIT +- https://arxiv.org/abs/2004.06465 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_spanish_es.md b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_spanish_es.md new file mode 100644 index 00000000000000..860003133ded44 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_dehate_mono_spanish_es.md @@ -0,0 +1,102 @@ +--- +layout: model +title: Spanish BertForSequenceClassification Cased model (from Hate-speech-CNERG) +author: John Snow Labs +name: bert_sequence_classifier_dehate_mono_spanish +date: 2023-10-25 +tags: [es, open_source, bert, sequence_classification, ner, onnx] +task: Named Entity Recognition +language: es +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `dehatebert-mono-spanish` is a Spanish model originally trained by `Hate-speech-CNERG`. + +## Predicted Entities + +`NON_HATE`, `HATE` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_dehate_mono_spanish_es_5.1.4_3.4_1698209098735.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_dehate_mono_spanish_es_5.1.4_3.4_1698209098735.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_dehate_mono_spanish","es") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_dehate_mono_spanish","es") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_dehate_mono_spanish| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|es| +|Size:|627.7 MB| +|Case sensitive:|true| +|Max sentence length:|128| + +## References + +References + +- https://huggingface.co/Hate-speech-CNERG/dehatebert-mono-spanish +- https://github.com/punyajoy/DE-LIMIT +- https://arxiv.org/abs/2004.06465 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_paraphrase_pt.md b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_paraphrase_pt.md new file mode 100644 index 00000000000000..c5ff6d7364ff75 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_paraphrase_pt.md @@ -0,0 +1,100 @@ +--- +layout: model +title: Portuguese BertForSequenceClassification Cased model (from Prompsit) +author: John Snow Labs +name: bert_sequence_classifier_paraphrase +date: 2023-10-25 +tags: [pt, open_source, bert, sequence_classification, ner, onnx] +task: Named Entity Recognition +language: pt +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `paraphrase-bert-pt` is a Portuguese model originally trained by `Prompsit`. + +## Predicted Entities + +`Not Paraphrase`, `Paraphrase` + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_paraphrase_pt_5.1.4_3.4_1698232661863.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_paraphrase_pt_5.1.4_3.4_1698232661863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python +documentAssembler = DocumentAssembler() \ + .setInputCol("text") \ + .setOutputCol("document") + +tokenizer = Tokenizer() \ + .setInputCols("document") \ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_paraphrase","pt") \ + .setInputCols(["document", "token"]) \ + .setOutputCol("class") + +pipeline = Pipeline(stages=[documentAssembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) +``` +```scala +val documentAssembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_paraphrase","pt") + .setInputCols(Array("document", "token")) + .setOutputCol("ner") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_paraphrase| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[document, token]| +|Output Labels:|[ner]| +|Language:|pt| +|Size:|408.2 MB| +|Case sensitive:|true| +|Max sentence length:|128| + +## References + +References + +- https://huggingface.co/Prompsit/paraphrase-bert-pt \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_clf_digimag_fa.md b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_clf_digimag_fa.md new file mode 100644 index 00000000000000..11ee443db9c24e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_clf_digimag_fa.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Persian bert_sequence_classifier_persian_farsi_base_uncased_clf_digimag BertForSequenceClassification from HooshvareLab +author: John Snow Labs +name: bert_sequence_classifier_persian_farsi_base_uncased_clf_digimag +date: 2023-10-25 +tags: [bert, fa, open_source, sequence_classification, onnx] +task: Text Classification +language: fa +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sequence_classifier_persian_farsi_base_uncased_clf_digimag` is a Persian model originally trained by HooshvareLab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_persian_farsi_base_uncased_clf_digimag_fa_5.1.4_3.4_1698209319334.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_persian_farsi_base_uncased_clf_digimag_fa_5.1.4_3.4_1698209319334.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_persian_farsi_base_uncased_clf_digimag","fa")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_persian_farsi_base_uncased_clf_digimag","fa") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_persian_farsi_base_uncased_clf_digimag| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|fa| +|Size:|608.7 MB| + +## References + +https://huggingface.co/HooshvareLab/bert-fa-base-uncased-clf-digimag \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_clf_persiannews_fa.md b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_clf_persiannews_fa.md new file mode 100644 index 00000000000000..d39d71ed0c475f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_clf_persiannews_fa.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Persian bert_sequence_classifier_persian_farsi_base_uncased_clf_persiannews BertForSequenceClassification from HooshvareLab +author: John Snow Labs +name: bert_sequence_classifier_persian_farsi_base_uncased_clf_persiannews +date: 2023-10-25 +tags: [bert, fa, open_source, sequence_classification, onnx] +task: Text Classification +language: fa +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sequence_classifier_persian_farsi_base_uncased_clf_persiannews` is a Persian model originally trained by HooshvareLab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_persian_farsi_base_uncased_clf_persiannews_fa_5.1.4_3.4_1698209556757.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_persian_farsi_base_uncased_clf_persiannews_fa_5.1.4_3.4_1698209556757.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_persian_farsi_base_uncased_clf_persiannews","fa")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_persian_farsi_base_uncased_clf_persiannews","fa") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_persian_farsi_base_uncased_clf_persiannews| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|fa| +|Size:|608.7 MB| + +## References + +https://huggingface.co/HooshvareLab/bert-fa-base-uncased-clf-persiannews \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_binary_fa.md b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_binary_fa.md new file mode 100644 index 00000000000000..17cc4aad219721 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_binary_fa.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Persian bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_binary BertForSequenceClassification from HooshvareLab +author: John Snow Labs +name: bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_binary +date: 2023-10-25 +tags: [bert, fa, open_source, sequence_classification, onnx] +task: Text Classification +language: fa +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_binary` is a Persian model originally trained by HooshvareLab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_binary_fa_5.1.4_3.4_1698209797867.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_binary_fa_5.1.4_3.4_1698209797867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_binary","fa")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_binary","fa") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_binary| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|fa| +|Size:|608.7 MB| + +## References + +https://huggingface.co/HooshvareLab/bert-fa-base-uncased-sentiment-deepsentipers-binary \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_multi_fa.md b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_multi_fa.md new file mode 100644 index 00000000000000..9feda5ef5fc54a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_multi_fa.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Persian bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_multi BertForSequenceClassification from HooshvareLab +author: John Snow Labs +name: bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_multi +date: 2023-10-25 +tags: [bert, fa, open_source, sequence_classification, onnx] +task: Text Classification +language: fa +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_multi` is a Persian model originally trained by HooshvareLab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_multi_fa_5.1.4_3.4_1698210004394.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_multi_fa_5.1.4_3.4_1698210004394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_multi","fa")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_multi","fa") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_persian_farsi_base_uncased_sentiment_deepsentipers_multi| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|fa| +|Size:|608.7 MB| + +## References + +https://huggingface.co/HooshvareLab/bert-fa-base-uncased-sentiment-deepsentipers-multi \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_sentiment_digikala_fa.md b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_sentiment_digikala_fa.md new file mode 100644 index 00000000000000..343b06b8e5ed38 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_sentiment_digikala_fa.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Persian bert_sequence_classifier_persian_farsi_base_uncased_sentiment_digikala BertForSequenceClassification from HooshvareLab +author: John Snow Labs +name: bert_sequence_classifier_persian_farsi_base_uncased_sentiment_digikala +date: 2023-10-25 +tags: [bert, fa, open_source, sequence_classification, onnx] +task: Text Classification +language: fa +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sequence_classifier_persian_farsi_base_uncased_sentiment_digikala` is a Persian model originally trained by HooshvareLab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_persian_farsi_base_uncased_sentiment_digikala_fa_5.1.4_3.4_1698210264996.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_persian_farsi_base_uncased_sentiment_digikala_fa_5.1.4_3.4_1698210264996.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_persian_farsi_base_uncased_sentiment_digikala","fa")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_persian_farsi_base_uncased_sentiment_digikala","fa") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_persian_farsi_base_uncased_sentiment_digikala| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|fa| +|Size:|608.7 MB| + +## References + +https://huggingface.co/HooshvareLab/bert-fa-base-uncased-sentiment-digikala \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_sentiment_snappfood_fa.md b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_sentiment_snappfood_fa.md new file mode 100644 index 00000000000000..85056d89c3ccd6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_sequence_classifier_persian_farsi_base_uncased_sentiment_snappfood_fa.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Persian bert_sequence_classifier_persian_farsi_base_uncased_sentiment_snappfood BertForSequenceClassification from HooshvareLab +author: John Snow Labs +name: bert_sequence_classifier_persian_farsi_base_uncased_sentiment_snappfood +date: 2023-10-25 +tags: [bert, fa, open_source, sequence_classification, onnx] +task: Text Classification +language: fa +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sequence_classifier_persian_farsi_base_uncased_sentiment_snappfood` is a Persian model originally trained by HooshvareLab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_persian_farsi_base_uncased_sentiment_snappfood_fa_5.1.4_3.4_1698210508316.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sequence_classifier_persian_farsi_base_uncased_sentiment_snappfood_fa_5.1.4_3.4_1698210508316.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_persian_farsi_base_uncased_sentiment_snappfood","fa")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sequence_classifier_persian_farsi_base_uncased_sentiment_snappfood","fa") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sequence_classifier_persian_farsi_base_uncased_sentiment_snappfood| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|fa| +|Size:|608.7 MB| + +## References + +https://huggingface.co/HooshvareLab/bert-fa-base-uncased-sentiment-snappfood \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_sim_doc_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_sim_doc_en.md new file mode 100644 index 00000000000000..b597749fd4d9d9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_sim_doc_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_sim_doc BertForSequenceClassification from LilaBoualili +author: John Snow Labs +name: bert_sim_doc +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sim_doc` is a English model originally trained by LilaBoualili. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sim_doc_en_5.1.4_3.4_1698221193643.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sim_doc_en_5.1.4_3.4_1698221193643.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sim_doc","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sim_doc","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sim_doc| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/LilaBoualili/bert-sim-doc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_sim_pair_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_sim_pair_en.md new file mode 100644 index 00000000000000..c3ebb2668186f8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_sim_pair_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_sim_pair BertForSequenceClassification from LilaBoualili +author: John Snow Labs +name: bert_sim_pair +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_sim_pair` is a English model originally trained by LilaBoualili. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_sim_pair_en_5.1.4_3.4_1698221374777.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_sim_pair_en_5.1.4_3.4_1698221374777.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_sim_pair","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_sim_pair","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_sim_pair| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/LilaBoualili/bert-sim-pair \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_finetuned_enron_spam_detection_mccoole_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_finetuned_enron_spam_detection_mccoole_en.md new file mode 100644 index 00000000000000..84fe5dccffb944 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_finetuned_enron_spam_detection_mccoole_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_tiny_finetuned_enron_spam_detection_mccoole BertForSequenceClassification from mccoole +author: John Snow Labs +name: bert_tiny_finetuned_enron_spam_detection_mccoole +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tiny_finetuned_enron_spam_detection_mccoole` is a English model originally trained by mccoole. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_finetuned_enron_spam_detection_mccoole_en_5.1.4_3.4_1698194499023.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_finetuned_enron_spam_detection_mccoole_en_5.1.4_3.4_1698194499023.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_tiny_finetuned_enron_spam_detection_mccoole","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_tiny_finetuned_enron_spam_detection_mccoole","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_tiny_finetuned_enron_spam_detection_mccoole| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/mccoole/bert-tiny-finetuned-enron-spam-detection \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_finetuned_mnli_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_finetuned_mnli_en.md new file mode 100644 index 00000000000000..4ce35b5fb49fc7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_finetuned_mnli_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_tiny_finetuned_mnli BertForSequenceClassification from M-FAC +author: John Snow Labs +name: bert_tiny_finetuned_mnli +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tiny_finetuned_mnli` is a English model originally trained by M-FAC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_finetuned_mnli_en_5.1.4_3.4_1698222635613.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_finetuned_mnli_en_5.1.4_3.4_1698222635613.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_tiny_finetuned_mnli","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_tiny_finetuned_mnli","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_tiny_finetuned_mnli| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/M-FAC/bert-tiny-finetuned-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_finetuned_mrpc_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_finetuned_mrpc_en.md new file mode 100644 index 00000000000000..bb433413792c4c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_finetuned_mrpc_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_tiny_finetuned_mrpc BertForSequenceClassification from M-FAC +author: John Snow Labs +name: bert_tiny_finetuned_mrpc +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tiny_finetuned_mrpc` is a English model originally trained by M-FAC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_finetuned_mrpc_en_5.1.4_3.4_1698222721542.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_finetuned_mrpc_en_5.1.4_3.4_1698222721542.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_tiny_finetuned_mrpc","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_tiny_finetuned_mrpc","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_tiny_finetuned_mrpc| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/M-FAC/bert-tiny-finetuned-mrpc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_finetuned_qnli_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_finetuned_qnli_en.md new file mode 100644 index 00000000000000..4ea066c989469b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_finetuned_qnli_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_tiny_finetuned_qnli BertForSequenceClassification from M-FAC +author: John Snow Labs +name: bert_tiny_finetuned_qnli +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tiny_finetuned_qnli` is a English model originally trained by M-FAC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_finetuned_qnli_en_5.1.4_3.4_1698222815267.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_finetuned_qnli_en_5.1.4_3.4_1698222815267.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_tiny_finetuned_qnli","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_tiny_finetuned_qnli","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_tiny_finetuned_qnli| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/M-FAC/bert-tiny-finetuned-qnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_finetuned_qqp_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_finetuned_qqp_en.md new file mode 100644 index 00000000000000..ffe2e048cb4561 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_finetuned_qqp_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_tiny_finetuned_qqp BertForSequenceClassification from M-FAC +author: John Snow Labs +name: bert_tiny_finetuned_qqp +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tiny_finetuned_qqp` is a English model originally trained by M-FAC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_finetuned_qqp_en_5.1.4_3.4_1698222915759.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_finetuned_qqp_en_5.1.4_3.4_1698222915759.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_tiny_finetuned_qqp","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_tiny_finetuned_qqp","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_tiny_finetuned_qqp| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/M-FAC/bert-tiny-finetuned-qqp \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_finetuned_sst2_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_finetuned_sst2_en.md new file mode 100644 index 00000000000000..119e41dac1f850 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_finetuned_sst2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_tiny_finetuned_sst2 BertForSequenceClassification from M-FAC +author: John Snow Labs +name: bert_tiny_finetuned_sst2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tiny_finetuned_sst2` is a English model originally trained by M-FAC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_finetuned_sst2_en_5.1.4_3.4_1698223010239.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_finetuned_sst2_en_5.1.4_3.4_1698223010239.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_tiny_finetuned_sst2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_tiny_finetuned_sst2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_tiny_finetuned_sst2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/M-FAC/bert-tiny-finetuned-sst2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_finetuned_stsb_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_finetuned_stsb_en.md new file mode 100644 index 00000000000000..b625afd2dd6355 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_finetuned_stsb_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_tiny_finetuned_stsb BertForSequenceClassification from M-FAC +author: John Snow Labs +name: bert_tiny_finetuned_stsb +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tiny_finetuned_stsb` is a English model originally trained by M-FAC. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_finetuned_stsb_en_5.1.4_3.4_1698223101321.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_finetuned_stsb_en_5.1.4_3.4_1698223101321.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_tiny_finetuned_stsb","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_tiny_finetuned_stsb","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_tiny_finetuned_stsb| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/M-FAC/bert-tiny-finetuned-stsb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_goodreads_wandb_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_goodreads_wandb_en.md new file mode 100644 index 00000000000000..0438af78995fcc --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_tiny_goodreads_wandb_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_tiny_goodreads_wandb BertForSequenceClassification from dhmeltzer +author: John Snow Labs +name: bert_tiny_goodreads_wandb +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tiny_goodreads_wandb` is a English model originally trained by dhmeltzer. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tiny_goodreads_wandb_en_5.1.4_3.4_1698263734400.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tiny_goodreads_wandb_en_5.1.4_3.4_1698263734400.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_tiny_goodreads_wandb","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_tiny_goodreads_wandb","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_tiny_goodreads_wandb| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/dhmeltzer/bert-tiny-goodreads-wandb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_tweets_semeval_clean_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_tweets_semeval_clean_en.md new file mode 100644 index 00000000000000..dbfdc496183c35 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_tweets_semeval_clean_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_tweets_semeval_clean BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_tweets_semeval_clean +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tweets_semeval_clean` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tweets_semeval_clean_en_5.1.4_3.4_1698201361960.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tweets_semeval_clean_en_5.1.4_3.4_1698201361960.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_tweets_semeval_clean","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_tweets_semeval_clean","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_tweets_semeval_clean| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-tweets-semeval-clean \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_tweets_semeval_unclean_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_tweets_semeval_unclean_en.md new file mode 100644 index 00000000000000..797d04bc672bb2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_tweets_semeval_unclean_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_tweets_semeval_unclean BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_tweets_semeval_unclean +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_tweets_semeval_unclean` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_tweets_semeval_unclean_en_5.1.4_3.4_1698201555184.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_tweets_semeval_unclean_en_5.1.4_3.4_1698201555184.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_tweets_semeval_unclean","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_tweets_semeval_unclean","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_tweets_semeval_unclean| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-tweets-semeval-unclean \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_vanilla_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_vanilla_en.md new file mode 100644 index 00000000000000..b0cec13a6b38c5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_vanilla_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_vanilla BertForSequenceClassification from LilaBoualili +author: John Snow Labs +name: bert_vanilla +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_vanilla` is a English model originally trained by LilaBoualili. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_vanilla_en_5.1.4_3.4_1698221552184.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_vanilla_en_5.1.4_3.4_1698221552184.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_vanilla","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_vanilla","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_vanilla| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/LilaBoualili/bert-vanilla \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_wiki_comments_finetuned_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_wiki_comments_finetuned_en.md new file mode 100644 index 00000000000000..255d344248db6b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_wiki_comments_finetuned_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_wiki_comments_finetuned BertForSequenceClassification from DoyyingFace +author: John Snow Labs +name: bert_wiki_comments_finetuned +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_wiki_comments_finetuned` is a English model originally trained by DoyyingFace. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_wiki_comments_finetuned_en_5.1.4_3.4_1698201749015.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_wiki_comments_finetuned_en_5.1.4_3.4_1698201749015.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_wiki_comments_finetuned","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_wiki_comments_finetuned","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_wiki_comments_finetuned| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/DoyyingFace/bert-wiki-comments-finetuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bert_wikipedia_sst2_en.md b/docs/_posts/ahmedlone127/2023-10-25-bert_wikipedia_sst2_en.md new file mode 100644 index 00000000000000..0decb892f3ea53 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bert_wikipedia_sst2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_wikipedia_sst2 BertForSequenceClassification from deepesh0x +author: John Snow Labs +name: bert_wikipedia_sst2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_wikipedia_sst2` is a English model originally trained by deepesh0x. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_wikipedia_sst2_en_5.1.4_3.4_1698211274392.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_wikipedia_sst2_en_5.1.4_3.4_1698211274392.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_wikipedia_sst2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_wikipedia_sst2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_wikipedia_sst2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/deepesh0x/bert_wikipedia_sst2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bertabaporu_portuguese_irony_en.md b/docs/_posts/ahmedlone127/2023-10-25-bertabaporu_portuguese_irony_en.md new file mode 100644 index 00000000000000..9f393d39e88ebc --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bertabaporu_portuguese_irony_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bertabaporu_portuguese_irony BertForSequenceClassification from pysentimiento +author: John Snow Labs +name: bertabaporu_portuguese_irony +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertabaporu_portuguese_irony` is a English model originally trained by pysentimiento. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertabaporu_portuguese_irony_en_5.1.4_3.4_1698227283769.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertabaporu_portuguese_irony_en_5.1.4_3.4_1698227283769.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bertabaporu_portuguese_irony","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bertabaporu_portuguese_irony","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bertabaporu_portuguese_irony| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|507.0 MB| + +## References + +https://huggingface.co/pysentimiento/bertabaporu-pt-irony \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bertimbau_hate_speech_en.md b/docs/_posts/ahmedlone127/2023-10-25-bertimbau_hate_speech_en.md new file mode 100644 index 00000000000000..b63f0e8192f2ad --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bertimbau_hate_speech_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bertimbau_hate_speech BertForSequenceClassification from Nelci +author: John Snow Labs +name: bertimbau_hate_speech +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertimbau_hate_speech` is a English model originally trained by Nelci. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertimbau_hate_speech_en_5.1.4_3.4_1698260945506.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertimbau_hate_speech_en_5.1.4_3.4_1698260945506.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bertimbau_hate_speech","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bertimbau_hate_speech","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bertimbau_hate_speech| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Nelci/bertimbau_hate_speech \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bertimbau_socioambiental_dandara_en.md b/docs/_posts/ahmedlone127/2023-10-25-bertimbau_socioambiental_dandara_en.md new file mode 100644 index 00000000000000..3faf7331925de6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bertimbau_socioambiental_dandara_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bertimbau_socioambiental_dandara BertForSequenceClassification from Dandara +author: John Snow Labs +name: bertimbau_socioambiental_dandara +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bertimbau_socioambiental_dandara` is a English model originally trained by Dandara. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bertimbau_socioambiental_dandara_en_5.1.4_3.4_1698193429174.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bertimbau_socioambiental_dandara_en_5.1.4_3.4_1698193429174.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bertimbau_socioambiental_dandara","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bertimbau_socioambiental_dandara","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bertimbau_socioambiental_dandara| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Dandara/bertimbau-socioambiental \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-binary_fully_trained_bert_en.md b/docs/_posts/ahmedlone127/2023-10-25-binary_fully_trained_bert_en.md new file mode 100644 index 00000000000000..07619fa7e4dc11 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-binary_fully_trained_bert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English binary_fully_trained_bert BertForSequenceClassification from SporkyToast +author: John Snow Labs +name: binary_fully_trained_bert +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`binary_fully_trained_bert` is a English model originally trained by SporkyToast. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/binary_fully_trained_bert_en_5.1.4_3.4_1698217058862.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/binary_fully_trained_bert_en_5.1.4_3.4_1698217058862.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("binary_fully_trained_bert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("binary_fully_trained_bert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|binary_fully_trained_bert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/SporkyToast/binary-fully-trained-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-biobert_base_cased_v1_2_finetuned_textclassification_en.md b/docs/_posts/ahmedlone127/2023-10-25-biobert_base_cased_v1_2_finetuned_textclassification_en.md new file mode 100644 index 00000000000000..e7002773f23e12 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-biobert_base_cased_v1_2_finetuned_textclassification_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English biobert_base_cased_v1_2_finetuned_textclassification BertForSequenceClassification from Kekelilii +author: John Snow Labs +name: biobert_base_cased_v1_2_finetuned_textclassification +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobert_base_cased_v1_2_finetuned_textclassification` is a English model originally trained by Kekelilii. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_base_cased_v1_2_finetuned_textclassification_en_5.1.4_3.4_1698196715226.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_base_cased_v1_2_finetuned_textclassification_en_5.1.4_3.4_1698196715226.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("biobert_base_cased_v1_2_finetuned_textclassification","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("biobert_base_cased_v1_2_finetuned_textclassification","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biobert_base_cased_v1_2_finetuned_textclassification| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Kekelilii/biobert-base-cased-v1.2_finetuned_TextClassification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-biobert_finetuned_genetic_mutation_en.md b/docs/_posts/ahmedlone127/2023-10-25-biobert_finetuned_genetic_mutation_en.md new file mode 100644 index 00000000000000..9a1ce98a172d31 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-biobert_finetuned_genetic_mutation_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English biobert_finetuned_genetic_mutation BertForSequenceClassification from wahdan99 +author: John Snow Labs +name: biobert_finetuned_genetic_mutation +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`biobert_finetuned_genetic_mutation` is a English model originally trained by wahdan99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/biobert_finetuned_genetic_mutation_en_5.1.4_3.4_1698224837394.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/biobert_finetuned_genetic_mutation_en_5.1.4_3.4_1698224837394.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("biobert_finetuned_genetic_mutation","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("biobert_finetuned_genetic_mutation","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|biobert_finetuned_genetic_mutation| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.3 MB| + +## References + +https://huggingface.co/wahdan99/biobert-finetuned-genetic-mutation \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bioclinical_bert_ft_m3_lc_en.md b/docs/_posts/ahmedlone127/2023-10-25-bioclinical_bert_ft_m3_lc_en.md new file mode 100644 index 00000000000000..623070620289b5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bioclinical_bert_ft_m3_lc_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bioclinical_bert_ft_m3_lc BertForSequenceClassification from sarahmiller137 +author: John Snow Labs +name: bioclinical_bert_ft_m3_lc +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bioclinical_bert_ft_m3_lc` is a English model originally trained by sarahmiller137. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bioclinical_bert_ft_m3_lc_en_5.1.4_3.4_1698213779941.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bioclinical_bert_ft_m3_lc_en_5.1.4_3.4_1698213779941.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bioclinical_bert_ft_m3_lc","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bioclinical_bert_ft_m3_lc","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bioclinical_bert_ft_m3_lc| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.5 MB| + +## References + +https://huggingface.co/sarahmiller137/bioclinical-bert-ft-m3-lc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bluebert_sitesentence_diagnosis_classification_en.md b/docs/_posts/ahmedlone127/2023-10-25-bluebert_sitesentence_diagnosis_classification_en.md new file mode 100644 index 00000000000000..a99e900bb220ec --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bluebert_sitesentence_diagnosis_classification_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bluebert_sitesentence_diagnosis_classification BertForSequenceClassification from DongHyoungLee +author: John Snow Labs +name: bluebert_sitesentence_diagnosis_classification +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bluebert_sitesentence_diagnosis_classification` is a English model originally trained by DongHyoungLee. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bluebert_sitesentence_diagnosis_classification_en_5.1.4_3.4_1698274392002.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bluebert_sitesentence_diagnosis_classification_en_5.1.4_3.4_1698274392002.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bluebert_sitesentence_diagnosis_classification","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bluebert_sitesentence_diagnosis_classification","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bluebert_sitesentence_diagnosis_classification| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.3 MB| + +## References + +https://huggingface.co/DongHyoungLee/bluebert-sitesentence-diagnosis-classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-boss_sentiment_bert_base_uncased_en.md b/docs/_posts/ahmedlone127/2023-10-25-boss_sentiment_bert_base_uncased_en.md new file mode 100644 index 00000000000000..13522eff0e11e1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-boss_sentiment_bert_base_uncased_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English boss_sentiment_bert_base_uncased BertForSequenceClassification from Kyle1668 +author: John Snow Labs +name: boss_sentiment_bert_base_uncased +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`boss_sentiment_bert_base_uncased` is a English model originally trained by Kyle1668. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/boss_sentiment_bert_base_uncased_en_5.1.4_3.4_1698221348012.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/boss_sentiment_bert_base_uncased_en_5.1.4_3.4_1698221348012.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("boss_sentiment_bert_base_uncased","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("boss_sentiment_bert_base_uncased","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|boss_sentiment_bert_base_uncased| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Kyle1668/boss-sentiment-bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-boss_toxicity_bert_base_uncased_en.md b/docs/_posts/ahmedlone127/2023-10-25-boss_toxicity_bert_base_uncased_en.md new file mode 100644 index 00000000000000..376157fbf627b7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-boss_toxicity_bert_base_uncased_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English boss_toxicity_bert_base_uncased BertForSequenceClassification from Kyle1668 +author: John Snow Labs +name: boss_toxicity_bert_base_uncased +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`boss_toxicity_bert_base_uncased` is a English model originally trained by Kyle1668. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/boss_toxicity_bert_base_uncased_en_5.1.4_3.4_1698221527242.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/boss_toxicity_bert_base_uncased_en_5.1.4_3.4_1698221527242.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("boss_toxicity_bert_base_uncased","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("boss_toxicity_bert_base_uncased","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|boss_toxicity_bert_base_uncased| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Kyle1668/boss-toxicity-bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-bow_bert_en.md b/docs/_posts/ahmedlone127/2023-10-25-bow_bert_en.md new file mode 100644 index 00000000000000..cfb01eb65765aa --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-bow_bert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bow_bert BertForSequenceClassification from dmrau +author: John Snow Labs +name: bow_bert +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bow_bert` is a English model originally trained by dmrau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bow_bert_en_5.1.4_3.4_1698277505225.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bow_bert_en_5.1.4_3.4_1698277505225.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bow_bert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bow_bert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bow_bert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|408.1 MB| + +## References + +https://huggingface.co/dmrau/bow-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-burmese_bert_imdb_en.md b/docs/_posts/ahmedlone127/2023-10-25-burmese_bert_imdb_en.md new file mode 100644 index 00000000000000..1647260b17dd3c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-burmese_bert_imdb_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English burmese_bert_imdb BertForSequenceClassification from olesya2096 +author: John Snow Labs +name: burmese_bert_imdb +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`burmese_bert_imdb` is a English model originally trained by olesya2096. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/burmese_bert_imdb_en_5.1.4_3.4_1698209910704.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/burmese_bert_imdb_en_5.1.4_3.4_1698209910704.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("burmese_bert_imdb","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("burmese_bert_imdb","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|burmese_bert_imdb| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/olesya2096/my_bert_imdb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-chinese_roberta_wwm_ext_finetuned_binary_en.md b/docs/_posts/ahmedlone127/2023-10-25-chinese_roberta_wwm_ext_finetuned_binary_en.md new file mode 100644 index 00000000000000..c4d3f7d814634f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-chinese_roberta_wwm_ext_finetuned_binary_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English chinese_roberta_wwm_ext_finetuned_binary BertForSequenceClassification from Raychanan +author: John Snow Labs +name: chinese_roberta_wwm_ext_finetuned_binary +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`chinese_roberta_wwm_ext_finetuned_binary` is a English model originally trained by Raychanan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/chinese_roberta_wwm_ext_finetuned_binary_en_5.1.4_3.4_1698235230260.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/chinese_roberta_wwm_ext_finetuned_binary_en_5.1.4_3.4_1698235230260.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("chinese_roberta_wwm_ext_finetuned_binary","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("chinese_roberta_wwm_ext_finetuned_binary","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|chinese_roberta_wwm_ext_finetuned_binary| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.2 MB| + +## References + +https://huggingface.co/Raychanan/chinese-roberta-wwm-ext-FineTuned-Binary \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-codenlbert_samoan_en.md b/docs/_posts/ahmedlone127/2023-10-25-codenlbert_samoan_en.md new file mode 100644 index 00000000000000..6d7bf7dbdd7742 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-codenlbert_samoan_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English codenlbert_samoan BertForSequenceClassification from vishnun +author: John Snow Labs +name: codenlbert_samoan +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`codenlbert_samoan` is a English model originally trained by vishnun. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/codenlbert_samoan_en_5.1.4_3.4_1698206525278.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/codenlbert_samoan_en_5.1.4_3.4_1698206525278.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("codenlbert_samoan","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("codenlbert_samoan","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|codenlbert_samoan| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|107.9 MB| + +## References + +https://huggingface.co/vishnun/codenlbert-sm \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-codenlbert_tiny_en.md b/docs/_posts/ahmedlone127/2023-10-25-codenlbert_tiny_en.md new file mode 100644 index 00000000000000..ecfe9c17439701 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-codenlbert_tiny_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English codenlbert_tiny BertForSequenceClassification from vishnun +author: John Snow Labs +name: codenlbert_tiny +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`codenlbert_tiny` is a English model originally trained by vishnun. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/codenlbert_tiny_en_5.1.4_3.4_1698215047894.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/codenlbert_tiny_en_5.1.4_3.4_1698215047894.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("codenlbert_tiny","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("codenlbert_tiny","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|codenlbert_tiny| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/vishnun/codenlbert-tiny \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-covid_bert_e3_b16_v2_w0_01_dev1_en.md b/docs/_posts/ahmedlone127/2023-10-25-covid_bert_e3_b16_v2_w0_01_dev1_en.md new file mode 100644 index 00000000000000..156d554e246d15 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-covid_bert_e3_b16_v2_w0_01_dev1_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English covid_bert_e3_b16_v2_w0_01_dev1 BertForSequenceClassification from JerryYanJiang +author: John Snow Labs +name: covid_bert_e3_b16_v2_w0_01_dev1 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_bert_e3_b16_v2_w0_01_dev1` is a English model originally trained by JerryYanJiang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_bert_e3_b16_v2_w0_01_dev1_en_5.1.4_3.4_1698198314583.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_bert_e3_b16_v2_w0_01_dev1_en_5.1.4_3.4_1698198314583.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("covid_bert_e3_b16_v2_w0_01_dev1","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("covid_bert_e3_b16_v2_w0_01_dev1","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|covid_bert_e3_b16_v2_w0_01_dev1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/JerryYanJiang/covid_bert-e3-b16-v2-w0.01-dev1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-covid_twitter_bert_v2_1_4_2e_05_0_01_en.md b/docs/_posts/ahmedlone127/2023-10-25-covid_twitter_bert_v2_1_4_2e_05_0_01_en.md new file mode 100644 index 00000000000000..266876cec82bdd --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-covid_twitter_bert_v2_1_4_2e_05_0_01_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English covid_twitter_bert_v2_1_4_2e_05_0_01 BertForSequenceClassification from JerryYanJiang +author: John Snow Labs +name: covid_twitter_bert_v2_1_4_2e_05_0_01 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_twitter_bert_v2_1_4_2e_05_0_01` is a English model originally trained by JerryYanJiang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_twitter_bert_v2_1_4_2e_05_0_01_en_5.1.4_3.4_1698219195720.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_twitter_bert_v2_1_4_2e_05_0_01_en_5.1.4_3.4_1698219195720.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("covid_twitter_bert_v2_1_4_2e_05_0_01","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("covid_twitter_bert_v2_1_4_2e_05_0_01","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|covid_twitter_bert_v2_1_4_2e_05_0_01| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/JerryYanJiang/covid-twitter-bert-v2_1_4_2e-05_0.01 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-covid_twitter_bert_v2_3_4_2e_05_0_01_en.md b/docs/_posts/ahmedlone127/2023-10-25-covid_twitter_bert_v2_3_4_2e_05_0_01_en.md new file mode 100644 index 00000000000000..6c94172b3aae02 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-covid_twitter_bert_v2_3_4_2e_05_0_01_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English covid_twitter_bert_v2_3_4_2e_05_0_01 BertForSequenceClassification from JerryYanJiang +author: John Snow Labs +name: covid_twitter_bert_v2_3_4_2e_05_0_01 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_twitter_bert_v2_3_4_2e_05_0_01` is a English model originally trained by JerryYanJiang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_twitter_bert_v2_3_4_2e_05_0_01_en_5.1.4_3.4_1698218094936.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_twitter_bert_v2_3_4_2e_05_0_01_en_5.1.4_3.4_1698218094936.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("covid_twitter_bert_v2_3_4_2e_05_0_01","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("covid_twitter_bert_v2_3_4_2e_05_0_01","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|covid_twitter_bert_v2_3_4_2e_05_0_01| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/JerryYanJiang/covid-twitter-bert-v2_3_4_2e-05_0.01 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-covid_twitter_bert_v2_epoch3_batch4_lr2e_05_w0_01_en.md b/docs/_posts/ahmedlone127/2023-10-25-covid_twitter_bert_v2_epoch3_batch4_lr2e_05_w0_01_en.md new file mode 100644 index 00000000000000..5376352c5b5c55 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-covid_twitter_bert_v2_epoch3_batch4_lr2e_05_w0_01_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English covid_twitter_bert_v2_epoch3_batch4_lr2e_05_w0_01 BertForSequenceClassification from JerryYanJiang +author: John Snow Labs +name: covid_twitter_bert_v2_epoch3_batch4_lr2e_05_w0_01 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_twitter_bert_v2_epoch3_batch4_lr2e_05_w0_01` is a English model originally trained by JerryYanJiang. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_twitter_bert_v2_epoch3_batch4_lr2e_05_w0_01_en_5.1.4_3.4_1698217732233.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_twitter_bert_v2_epoch3_batch4_lr2e_05_w0_01_en_5.1.4_3.4_1698217732233.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("covid_twitter_bert_v2_epoch3_batch4_lr2e_05_w0_01","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("covid_twitter_bert_v2_epoch3_batch4_lr2e_05_w0_01","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|covid_twitter_bert_v2_epoch3_batch4_lr2e_05_w0_01| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/JerryYanJiang/covid-twitter-bert-v2_epoch3_batch4_lr2e-05_w0.01 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-covid_twitter_bert_v2_mnli_nli_sts_crossencoder_covid_hera_en.md b/docs/_posts/ahmedlone127/2023-10-25-covid_twitter_bert_v2_mnli_nli_sts_crossencoder_covid_hera_en.md new file mode 100644 index 00000000000000..64d2a043d42408 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-covid_twitter_bert_v2_mnli_nli_sts_crossencoder_covid_hera_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English covid_twitter_bert_v2_mnli_nli_sts_crossencoder_covid_hera BertForSequenceClassification from liyijing024 +author: John Snow Labs +name: covid_twitter_bert_v2_mnli_nli_sts_crossencoder_covid_hera +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covid_twitter_bert_v2_mnli_nli_sts_crossencoder_covid_hera` is a English model originally trained by liyijing024. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covid_twitter_bert_v2_mnli_nli_sts_crossencoder_covid_hera_en_5.1.4_3.4_1698237356534.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covid_twitter_bert_v2_mnli_nli_sts_crossencoder_covid_hera_en_5.1.4_3.4_1698237356534.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("covid_twitter_bert_v2_mnli_nli_sts_crossencoder_covid_hera","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("covid_twitter_bert_v2_mnli_nli_sts_crossencoder_covid_hera","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|covid_twitter_bert_v2_mnli_nli_sts_crossencoder_covid_hera| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/liyijing024/covid-twitter-bert-v2-mnli-NLI-STS-CrossEncoder-Covid-HeRA \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-covidbert_medmarco_en.md b/docs/_posts/ahmedlone127/2023-10-25-covidbert_medmarco_en.md new file mode 100644 index 00000000000000..9279c7c1c4c9f7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-covidbert_medmarco_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English covidbert_medmarco BertForSequenceClassification from Darkrider +author: John Snow Labs +name: covidbert_medmarco +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`covidbert_medmarco` is a English model originally trained by Darkrider. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/covidbert_medmarco_en_5.1.4_3.4_1698193642559.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/covidbert_medmarco_en_5.1.4_3.4_1698193642559.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("covidbert_medmarco","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("covidbert_medmarco","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|covidbert_medmarco| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Darkrider/covidbert_medmarco \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-cq_bert_model_repo_en.md b/docs/_posts/ahmedlone127/2023-10-25-cq_bert_model_repo_en.md new file mode 100644 index 00000000000000..0ab7e9cf889a79 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-cq_bert_model_repo_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English cq_bert_model_repo BertForSequenceClassification from GD +author: John Snow Labs +name: cq_bert_model_repo +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`cq_bert_model_repo` is a English model originally trained by GD. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/cq_bert_model_repo_en_5.1.4_3.4_1698204629269.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/cq_bert_model_repo_en_5.1.4_3.4_1698204629269.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("cq_bert_model_repo","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("cq_bert_model_repo","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|cq_bert_model_repo| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/GD/cq-bert-model-repo \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-deprem_bert_128k_tr.md b/docs/_posts/ahmedlone127/2023-10-25-deprem_bert_128k_tr.md new file mode 100644 index 00000000000000..8577d498ed5786 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-deprem_bert_128k_tr.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Turkish deprem_bert_128k BertForSequenceClassification from deprem-ml +author: John Snow Labs +name: deprem_bert_128k +date: 2023-10-25 +tags: [bert, tr, open_source, sequence_classification, onnx] +task: Text Classification +language: tr +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deprem_bert_128k` is a Turkish model originally trained by deprem-ml. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deprem_bert_128k_tr_5.1.4_3.4_1698207573310.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deprem_bert_128k_tr_5.1.4_3.4_1698207573310.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("deprem_bert_128k","tr")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("deprem_bert_128k","tr") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deprem_bert_128k| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|tr| +|Size:|691.6 MB| + +## References + +https://huggingface.co/deprem-ml/deprem_bert_128k \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-deprem_bert_128k_v13_beta_tr.md b/docs/_posts/ahmedlone127/2023-10-25-deprem_bert_128k_v13_beta_tr.md new file mode 100644 index 00000000000000..e6d50643bdfe97 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-deprem_bert_128k_v13_beta_tr.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Turkish deprem_bert_128k_v13_beta BertForSequenceClassification from deprem-ml +author: John Snow Labs +name: deprem_bert_128k_v13_beta +date: 2023-10-25 +tags: [bert, tr, open_source, sequence_classification, onnx] +task: Text Classification +language: tr +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deprem_bert_128k_v13_beta` is a Turkish model originally trained by deprem-ml. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deprem_bert_128k_v13_beta_tr_5.1.4_3.4_1698210154059.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deprem_bert_128k_v13_beta_tr_5.1.4_3.4_1698210154059.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("deprem_bert_128k_v13_beta","tr")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("deprem_bert_128k_v13_beta","tr") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deprem_bert_128k_v13_beta| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|tr| +|Size:|691.6 MB| + +## References + +https://huggingface.co/deprem-ml/deprem_bert_128k_v13_beta \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-deprem_bert_128k_v2_tr.md b/docs/_posts/ahmedlone127/2023-10-25-deprem_bert_128k_v2_tr.md new file mode 100644 index 00000000000000..8b46e294d08853 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-deprem_bert_128k_v2_tr.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Turkish deprem_bert_128k_v2 BertForSequenceClassification from Ertugrul +author: John Snow Labs +name: deprem_bert_128k_v2 +date: 2023-10-25 +tags: [bert, tr, open_source, sequence_classification, onnx] +task: Text Classification +language: tr +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deprem_bert_128k_v2` is a Turkish model originally trained by Ertugrul. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deprem_bert_128k_v2_tr_5.1.4_3.4_1698209721249.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deprem_bert_128k_v2_tr_5.1.4_3.4_1698209721249.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("deprem_bert_128k_v2","tr")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("deprem_bert_128k_v2","tr") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deprem_bert_128k_v2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|tr| +|Size:|691.6 MB| + +## References + +https://huggingface.co/Ertugrul/deprem_bert_128k_v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-deprem_berturk_binary_tr.md b/docs/_posts/ahmedlone127/2023-10-25-deprem_berturk_binary_tr.md new file mode 100644 index 00000000000000..93a6c5af8e4e43 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-deprem_berturk_binary_tr.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Turkish deprem_berturk_binary BertForSequenceClassification from ctoraman +author: John Snow Labs +name: deprem_berturk_binary +date: 2023-10-25 +tags: [bert, tr, open_source, sequence_classification, onnx] +task: Text Classification +language: tr +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`deprem_berturk_binary` is a Turkish model originally trained by ctoraman. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/deprem_berturk_binary_tr_5.1.4_3.4_1698218881162.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/deprem_berturk_binary_tr_5.1.4_3.4_1698218881162.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("deprem_berturk_binary","tr")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("deprem_berturk_binary","tr") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|deprem_berturk_binary| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|tr| +|Size:|414.5 MB| + +## References + +https://huggingface.co/ctoraman/deprem-berturk-binary \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-distillprotbert_knots_norwegian_fragments_en.md b/docs/_posts/ahmedlone127/2023-10-25-distillprotbert_knots_norwegian_fragments_en.md new file mode 100644 index 00000000000000..f1d2879604be78 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-distillprotbert_knots_norwegian_fragments_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English distillprotbert_knots_norwegian_fragments BertForSequenceClassification from roa7n +author: John Snow Labs +name: distillprotbert_knots_norwegian_fragments +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`distillprotbert_knots_norwegian_fragments` is a English model originally trained by roa7n. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/distillprotbert_knots_norwegian_fragments_en_5.1.4_3.4_1698199593701.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/distillprotbert_knots_norwegian_fragments_en_5.1.4_3.4_1698199593701.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("distillprotbert_knots_norwegian_fragments","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("distillprotbert_knots_norwegian_fragments","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|distillprotbert_knots_norwegian_fragments| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|864.5 MB| + +## References + +https://huggingface.co/roa7n/distillprotbert_knots_no_fragments \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-dk_emotion_bert_2_en.md b/docs/_posts/ahmedlone127/2023-10-25-dk_emotion_bert_2_en.md new file mode 100644 index 00000000000000..4953bc34c7f514 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-dk_emotion_bert_2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English dk_emotion_bert_2 BertForSequenceClassification from Only-Mike +author: John Snow Labs +name: dk_emotion_bert_2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dk_emotion_bert_2` is a English model originally trained by Only-Mike. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dk_emotion_bert_2_en_5.1.4_3.4_1698223071802.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dk_emotion_bert_2_en_5.1.4_3.4_1698223071802.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("dk_emotion_bert_2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("dk_emotion_bert_2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dk_emotion_bert_2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.6 MB| + +## References + +https://huggingface.co/Only-Mike/dk_emotion_bert_2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-dk_emotion_bert_class_en.md b/docs/_posts/ahmedlone127/2023-10-25-dk_emotion_bert_class_en.md new file mode 100644 index 00000000000000..5bb80989303491 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-dk_emotion_bert_class_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English dk_emotion_bert_class BertForSequenceClassification from Korsholm22 +author: John Snow Labs +name: dk_emotion_bert_class +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dk_emotion_bert_class` is a English model originally trained by Korsholm22. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dk_emotion_bert_class_en_5.1.4_3.4_1698222898858.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dk_emotion_bert_class_en_5.1.4_3.4_1698222898858.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("dk_emotion_bert_class","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("dk_emotion_bert_class","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dk_emotion_bert_class| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.6 MB| + +## References + +https://huggingface.co/Korsholm22/dk_emotion_bert_class \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-dkbert_hatespeech_detection_da.md b/docs/_posts/ahmedlone127/2023-10-25-dkbert_hatespeech_detection_da.md new file mode 100644 index 00000000000000..ca972e4669cd04 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-dkbert_hatespeech_detection_da.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Danish dkbert_hatespeech_detection BertForSequenceClassification from Guscode +author: John Snow Labs +name: dkbert_hatespeech_detection +date: 2023-10-25 +tags: [bert, da, open_source, sequence_classification, onnx] +task: Text Classification +language: da +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dkbert_hatespeech_detection` is a Danish model originally trained by Guscode. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dkbert_hatespeech_detection_da_5.1.4_3.4_1698205032220.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dkbert_hatespeech_detection_da_5.1.4_3.4_1698205032220.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("dkbert_hatespeech_detection","da")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("dkbert_hatespeech_detection","da") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dkbert_hatespeech_detection| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|da| +|Size:|414.5 MB| + +## References + +https://huggingface.co/Guscode/DKbert-hatespeech-detection \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-dutch_bert_en.md b/docs/_posts/ahmedlone127/2023-10-25-dutch_bert_en.md new file mode 100644 index 00000000000000..2c07f84e18a9e6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-dutch_bert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English dutch_bert BertForSequenceClassification from thearod5 +author: John Snow Labs +name: dutch_bert +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dutch_bert` is a English model originally trained by thearod5. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dutch_bert_en_5.1.4_3.4_1698200441893.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dutch_bert_en_5.1.4_3.4_1698200441893.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("dutch_bert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("dutch_bert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dutch_bert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/thearod5/nl-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-elvis_bert_base_en.md b/docs/_posts/ahmedlone127/2023-10-25-elvis_bert_base_en.md new file mode 100644 index 00000000000000..59d151974952cb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-elvis_bert_base_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English elvis_bert_base BertForSequenceClassification from elvis-d +author: John Snow Labs +name: elvis_bert_base +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`elvis_bert_base` is a English model originally trained by elvis-d. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/elvis_bert_base_en_5.1.4_3.4_1698192917559.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/elvis_bert_base_en_5.1.4_3.4_1698192917559.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("elvis_bert_base","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("elvis_bert_base","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|elvis_bert_base| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/elvis-d/elvis_bert_base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-emobert_single_binary_en.md b/docs/_posts/ahmedlone127/2023-10-25-emobert_single_binary_en.md new file mode 100644 index 00000000000000..350a5b6314ad2b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-emobert_single_binary_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English emobert_single_binary BertForSequenceClassification from reallycarlaost +author: John Snow Labs +name: emobert_single_binary +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emobert_single_binary` is a English model originally trained by reallycarlaost. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emobert_single_binary_en_5.1.4_3.4_1698246867339.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emobert_single_binary_en_5.1.4_3.4_1698246867339.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("emobert_single_binary","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("emobert_single_binary","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|emobert_single_binary| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/reallycarlaost/emobert-single-binary \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-emobert_valence_5_en.md b/docs/_posts/ahmedlone127/2023-10-25-emobert_valence_5_en.md new file mode 100644 index 00000000000000..118a846cb459a7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-emobert_valence_5_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English emobert_valence_5 BertForSequenceClassification from reallycarlaost +author: John Snow Labs +name: emobert_valence_5 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emobert_valence_5` is a English model originally trained by reallycarlaost. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emobert_valence_5_en_5.1.4_3.4_1698252491551.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emobert_valence_5_en_5.1.4_3.4_1698252491551.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("emobert_valence_5","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("emobert_valence_5","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|emobert_valence_5| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/reallycarlaost/emobert-valence-5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-emotion_classification_bert_base_en.md b/docs/_posts/ahmedlone127/2023-10-25-emotion_classification_bert_base_en.md new file mode 100644 index 00000000000000..4b48bb4d18e00a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-emotion_classification_bert_base_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English emotion_classification_bert_base BertForSequenceClassification from EasthShin +author: John Snow Labs +name: emotion_classification_bert_base +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`emotion_classification_bert_base` is a English model originally trained by EasthShin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/emotion_classification_bert_base_en_5.1.4_3.4_1698202284372.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/emotion_classification_bert_base_en_5.1.4_3.4_1698202284372.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("emotion_classification_bert_base","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("emotion_classification_bert_base","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|emotion_classification_bert_base| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/EasthShin/Emotion-Classification-bert-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-esg_bert_sector_classifier_en.md b/docs/_posts/ahmedlone127/2023-10-25-esg_bert_sector_classifier_en.md new file mode 100644 index 00000000000000..9d2530e3eb06d4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-esg_bert_sector_classifier_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English esg_bert_sector_classifier BertForSequenceClassification from ppsingh +author: John Snow Labs +name: esg_bert_sector_classifier +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esg_bert_sector_classifier` is a English model originally trained by ppsingh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esg_bert_sector_classifier_en_5.1.4_3.4_1698229025440.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esg_bert_sector_classifier_en_5.1.4_3.4_1698229025440.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("esg_bert_sector_classifier","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("esg_bert_sector_classifier","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|esg_bert_sector_classifier| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.8 MB| + +## References + +https://huggingface.co/ppsingh/esg-bert-sector-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-esgbert1_en.md b/docs/_posts/ahmedlone127/2023-10-25-esgbert1_en.md new file mode 100644 index 00000000000000..ddbd10adcb665e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-esgbert1_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English esgbert1 BertForSequenceClassification from owen198 +author: John Snow Labs +name: esgbert1 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esgbert1` is a English model originally trained by owen198. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esgbert1_en_5.1.4_3.4_1698270135920.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esgbert1_en_5.1.4_3.4_1698270135920.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("esgbert1","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("esgbert1","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|esgbert1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/owen198/esgbert1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-esgbert_en.md b/docs/_posts/ahmedlone127/2023-10-25-esgbert_en.md new file mode 100644 index 00000000000000..45ddd7a39d9e87 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-esgbert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English esgbert BertForSequenceClassification from owen198 +author: John Snow Labs +name: esgbert +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`esgbert` is a English model originally trained by owen198. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/esgbert_en_5.1.4_3.4_1698218399670.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/esgbert_en_5.1.4_3.4_1698218399670.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("esgbert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("esgbert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|esgbert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/owen198/esgbert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-fbert_ai_en.md b/docs/_posts/ahmedlone127/2023-10-25-fbert_ai_en.md new file mode 100644 index 00000000000000..423e422507bb80 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-fbert_ai_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English fbert_ai BertForSequenceClassification from wilburchen42 +author: John Snow Labs +name: fbert_ai +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fbert_ai` is a English model originally trained by wilburchen42. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fbert_ai_en_5.1.4_3.4_1698203738918.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fbert_ai_en_5.1.4_3.4_1698203738918.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("fbert_ai","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fbert_ai","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fbert_ai| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.6 MB| + +## References + +https://huggingface.co/wilburchen42/fbert-ai \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-fbert_aiclass_en.md b/docs/_posts/ahmedlone127/2023-10-25-fbert_aiclass_en.md new file mode 100644 index 00000000000000..1f24a4bca649d0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-fbert_aiclass_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English fbert_aiclass BertForSequenceClassification from wilburchen42 +author: John Snow Labs +name: fbert_aiclass +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fbert_aiclass` is a English model originally trained by wilburchen42. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fbert_aiclass_en_5.1.4_3.4_1698204182166.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fbert_aiclass_en_5.1.4_3.4_1698204182166.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("fbert_aiclass","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fbert_aiclass","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fbert_aiclass| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.6 MB| + +## References + +https://huggingface.co/wilburchen42/fbert-aiclass \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-finbert_finetuned_fg_single_sentence_news_weighted_en.md b/docs/_posts/ahmedlone127/2023-10-25-finbert_finetuned_fg_single_sentence_news_weighted_en.md new file mode 100644 index 00000000000000..5e6e199c7e098c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-finbert_finetuned_fg_single_sentence_news_weighted_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English finbert_finetuned_fg_single_sentence_news_weighted BertForSequenceClassification from lucaordronneau +author: John Snow Labs +name: finbert_finetuned_fg_single_sentence_news_weighted +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finbert_finetuned_fg_single_sentence_news_weighted` is a English model originally trained by lucaordronneau. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finbert_finetuned_fg_single_sentence_news_weighted_en_5.1.4_3.4_1698241050659.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finbert_finetuned_fg_single_sentence_news_weighted_en_5.1.4_3.4_1698241050659.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("finbert_finetuned_fg_single_sentence_news_weighted","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finbert_finetuned_fg_single_sentence_news_weighted","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finbert_finetuned_fg_single_sentence_news_weighted| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/lucaordronneau/finbert-finetuned-FG-SINGLE_SENTENCE-NEWS-WEIGHTED \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-finbert_fls_en.md b/docs/_posts/ahmedlone127/2023-10-25-finbert_fls_en.md new file mode 100644 index 00000000000000..db3949ce9f2f7a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-finbert_fls_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English finbert_fls BertForSequenceClassification from yiyanghkust +author: John Snow Labs +name: finbert_fls +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finbert_fls` is a English model originally trained by yiyanghkust. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finbert_fls_en_5.1.4_3.4_1698245276476.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finbert_fls_en_5.1.4_3.4_1698245276476.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("finbert_fls","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finbert_fls","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finbert_fls| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.6 MB| + +## References + +https://huggingface.co/yiyanghkust/finbert-fls \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-finbert_narsil_en.md b/docs/_posts/ahmedlone127/2023-10-25-finbert_narsil_en.md new file mode 100644 index 00000000000000..8fb39c5f320655 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-finbert_narsil_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English finbert_narsil BertForSequenceClassification from Narsil +author: John Snow Labs +name: finbert_narsil +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finbert_narsil` is a English model originally trained by Narsil. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finbert_narsil_en_5.1.4_3.4_1698255147780.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finbert_narsil_en_5.1.4_3.4_1698255147780.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("finbert_narsil","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finbert_narsil","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finbert_narsil| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Narsil/finbert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-finbert_tsla_en.md b/docs/_posts/ahmedlone127/2023-10-25-finbert_tsla_en.md new file mode 100644 index 00000000000000..176cfc852a7972 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-finbert_tsla_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English finbert_tsla BertForSequenceClassification from Forturne +author: John Snow Labs +name: finbert_tsla +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finbert_tsla` is a English model originally trained by Forturne. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finbert_tsla_en_5.1.4_3.4_1698218209908.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finbert_tsla_en_5.1.4_3.4_1698218209908.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("finbert_tsla","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finbert_tsla","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finbert_tsla| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.6 MB| + +## References + +https://huggingface.co/Forturne/Finbert_TSLA \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-fine_tune_bert_combined_en.md b/docs/_posts/ahmedlone127/2023-10-25-fine_tune_bert_combined_en.md new file mode 100644 index 00000000000000..eb6b2eb65cfa90 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-fine_tune_bert_combined_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English fine_tune_bert_combined BertForSequenceClassification from nouman-10 +author: John Snow Labs +name: fine_tune_bert_combined +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tune_bert_combined` is a English model originally trained by nouman-10. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tune_bert_combined_en_5.1.4_3.4_1698278330419.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tune_bert_combined_en_5.1.4_3.4_1698278330419.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("fine_tune_bert_combined","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fine_tune_bert_combined","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tune_bert_combined| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/nouman-10/fine-tune-bert-combined \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-fine_tune_bert_exist_en.md b/docs/_posts/ahmedlone127/2023-10-25-fine_tune_bert_exist_en.md new file mode 100644 index 00000000000000..cf0ee67577c2ec --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-fine_tune_bert_exist_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English fine_tune_bert_exist BertForSequenceClassification from nouman-10 +author: John Snow Labs +name: fine_tune_bert_exist +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tune_bert_exist` is a English model originally trained by nouman-10. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tune_bert_exist_en_5.1.4_3.4_1698275174749.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tune_bert_exist_en_5.1.4_3.4_1698275174749.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("fine_tune_bert_exist","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fine_tune_bert_exist","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tune_bert_exist| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/nouman-10/fine-tune-bert-exist \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-fine_tune_mbert_exist_en.md b/docs/_posts/ahmedlone127/2023-10-25-fine_tune_mbert_exist_en.md new file mode 100644 index 00000000000000..016cc501da4abd --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-fine_tune_mbert_exist_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English fine_tune_mbert_exist BertForSequenceClassification from nouman-10 +author: John Snow Labs +name: fine_tune_mbert_exist +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tune_mbert_exist` is a English model originally trained by nouman-10. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tune_mbert_exist_en_5.1.4_3.4_1698277503542.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tune_mbert_exist_en_5.1.4_3.4_1698277503542.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("fine_tune_mbert_exist","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fine_tune_mbert_exist","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tune_mbert_exist| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|627.7 MB| + +## References + +https://huggingface.co/nouman-10/fine-tune-mbert-exist \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_augmented_with_indobert_base_uncased_afaji_en.md b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_augmented_with_indobert_base_uncased_afaji_en.md new file mode 100644 index 00000000000000..3980e5051c15b1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_augmented_with_indobert_base_uncased_afaji_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English fine_tuned_indonli_augmented_with_indobert_base_uncased_afaji BertForSequenceClassification from afaji +author: John Snow Labs +name: fine_tuned_indonli_augmented_with_indobert_base_uncased_afaji +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_indonli_augmented_with_indobert_base_uncased_afaji` is a English model originally trained by afaji. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_indonli_augmented_with_indobert_base_uncased_afaji_en_5.1.4_3.4_1698221048030.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_indonli_augmented_with_indobert_base_uncased_afaji_en_5.1.4_3.4_1698221048030.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_indonli_augmented_with_indobert_base_uncased_afaji","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_indonli_augmented_with_indobert_base_uncased_afaji","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_indonli_augmented_with_indobert_base_uncased_afaji| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|413.9 MB| + +## References + +https://huggingface.co/afaji/fine-tuned-IndoNLI-Augmented-with-indobert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_augmented_with_indobert_base_uncased_muhammadravi251001_en.md b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_augmented_with_indobert_base_uncased_muhammadravi251001_en.md new file mode 100644 index 00000000000000..99fe6e43b50a22 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_augmented_with_indobert_base_uncased_muhammadravi251001_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English fine_tuned_indonli_augmented_with_indobert_base_uncased_muhammadravi251001 BertForSequenceClassification from muhammadravi251001 +author: John Snow Labs +name: fine_tuned_indonli_augmented_with_indobert_base_uncased_muhammadravi251001 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_indonli_augmented_with_indobert_base_uncased_muhammadravi251001` is a English model originally trained by muhammadravi251001. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_indonli_augmented_with_indobert_base_uncased_muhammadravi251001_en_5.1.4_3.4_1698225941984.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_indonli_augmented_with_indobert_base_uncased_muhammadravi251001_en_5.1.4_3.4_1698225941984.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_indonli_augmented_with_indobert_base_uncased_muhammadravi251001","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_indonli_augmented_with_indobert_base_uncased_muhammadravi251001","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_indonli_augmented_with_indobert_base_uncased_muhammadravi251001| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|413.9 MB| + +## References + +https://huggingface.co/muhammadravi251001/fine-tuned-IndoNLI-Augmented-with-indobert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_augmented_with_indobert_large_p2_afaji_en.md b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_augmented_with_indobert_large_p2_afaji_en.md new file mode 100644 index 00000000000000..621d35e533a7d6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_augmented_with_indobert_large_p2_afaji_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English fine_tuned_indonli_augmented_with_indobert_large_p2_afaji BertForSequenceClassification from afaji +author: John Snow Labs +name: fine_tuned_indonli_augmented_with_indobert_large_p2_afaji +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_indonli_augmented_with_indobert_large_p2_afaji` is a English model originally trained by afaji. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_indonli_augmented_with_indobert_large_p2_afaji_en_5.1.4_3.4_1698220859599.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_indonli_augmented_with_indobert_large_p2_afaji_en_5.1.4_3.4_1698220859599.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_indonli_augmented_with_indobert_large_p2_afaji","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_indonli_augmented_with_indobert_large_p2_afaji","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_indonli_augmented_with_indobert_large_p2_afaji| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/afaji/fine-tuned-IndoNLI-Augmented-with-indobert-large-p2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_augmented_with_indobert_large_p2_muhammadravi251001_en.md b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_augmented_with_indobert_large_p2_muhammadravi251001_en.md new file mode 100644 index 00000000000000..94bba1b2d3c5b6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_augmented_with_indobert_large_p2_muhammadravi251001_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English fine_tuned_indonli_augmented_with_indobert_large_p2_muhammadravi251001 BertForSequenceClassification from muhammadravi251001 +author: John Snow Labs +name: fine_tuned_indonli_augmented_with_indobert_large_p2_muhammadravi251001 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_indonli_augmented_with_indobert_large_p2_muhammadravi251001` is a English model originally trained by muhammadravi251001. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_indonli_augmented_with_indobert_large_p2_muhammadravi251001_en_5.1.4_3.4_1698223677212.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_indonli_augmented_with_indobert_large_p2_muhammadravi251001_en_5.1.4_3.4_1698223677212.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_indonli_augmented_with_indobert_large_p2_muhammadravi251001","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_indonli_augmented_with_indobert_large_p2_muhammadravi251001","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_indonli_augmented_with_indobert_large_p2_muhammadravi251001| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/muhammadravi251001/fine-tuned-IndoNLI-Augmented-with-indobert-large-p2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_basic_with_indobert_base_uncased_afaji_en.md b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_basic_with_indobert_base_uncased_afaji_en.md new file mode 100644 index 00000000000000..c8a49a6f970488 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_basic_with_indobert_base_uncased_afaji_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English fine_tuned_indonli_basic_with_indobert_base_uncased_afaji BertForSequenceClassification from afaji +author: John Snow Labs +name: fine_tuned_indonli_basic_with_indobert_base_uncased_afaji +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_indonli_basic_with_indobert_base_uncased_afaji` is a English model originally trained by afaji. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_indonli_basic_with_indobert_base_uncased_afaji_en_5.1.4_3.4_1698219271386.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_indonli_basic_with_indobert_base_uncased_afaji_en_5.1.4_3.4_1698219271386.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_indonli_basic_with_indobert_base_uncased_afaji","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_indonli_basic_with_indobert_base_uncased_afaji","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_indonli_basic_with_indobert_base_uncased_afaji| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|413.9 MB| + +## References + +https://huggingface.co/afaji/fine-tuned-IndoNLI-Basic-with-indobert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_basic_with_indobert_base_uncased_muhammadravi251001_en.md b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_basic_with_indobert_base_uncased_muhammadravi251001_en.md new file mode 100644 index 00000000000000..ff7efc7423853a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_basic_with_indobert_base_uncased_muhammadravi251001_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English fine_tuned_indonli_basic_with_indobert_base_uncased_muhammadravi251001 BertForSequenceClassification from muhammadravi251001 +author: John Snow Labs +name: fine_tuned_indonli_basic_with_indobert_base_uncased_muhammadravi251001 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_indonli_basic_with_indobert_base_uncased_muhammadravi251001` is a English model originally trained by muhammadravi251001. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_indonli_basic_with_indobert_base_uncased_muhammadravi251001_en_5.1.4_3.4_1698225044555.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_indonli_basic_with_indobert_base_uncased_muhammadravi251001_en_5.1.4_3.4_1698225044555.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_indonli_basic_with_indobert_base_uncased_muhammadravi251001","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_indonli_basic_with_indobert_base_uncased_muhammadravi251001","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_indonli_basic_with_indobert_base_uncased_muhammadravi251001| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|413.9 MB| + +## References + +https://huggingface.co/muhammadravi251001/fine-tuned-IndoNLI-Basic-with-indobert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_basic_with_indobert_large_p2_afaji_en.md b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_basic_with_indobert_large_p2_afaji_en.md new file mode 100644 index 00000000000000..60ae6ef7cfe365 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_basic_with_indobert_large_p2_afaji_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English fine_tuned_indonli_basic_with_indobert_large_p2_afaji BertForSequenceClassification from afaji +author: John Snow Labs +name: fine_tuned_indonli_basic_with_indobert_large_p2_afaji +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_indonli_basic_with_indobert_large_p2_afaji` is a English model originally trained by afaji. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_indonli_basic_with_indobert_large_p2_afaji_en_5.1.4_3.4_1698219934268.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_indonli_basic_with_indobert_large_p2_afaji_en_5.1.4_3.4_1698219934268.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_indonli_basic_with_indobert_large_p2_afaji","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_indonli_basic_with_indobert_large_p2_afaji","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_indonli_basic_with_indobert_large_p2_afaji| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/afaji/fine-tuned-IndoNLI-Basic-with-indobert-large-p2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_basic_with_indobert_large_p2_muhammadravi251001_en.md b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_basic_with_indobert_large_p2_muhammadravi251001_en.md new file mode 100644 index 00000000000000..4fc489ec386c5c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_basic_with_indobert_large_p2_muhammadravi251001_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English fine_tuned_indonli_basic_with_indobert_large_p2_muhammadravi251001 BertForSequenceClassification from muhammadravi251001 +author: John Snow Labs +name: fine_tuned_indonli_basic_with_indobert_large_p2_muhammadravi251001 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_indonli_basic_with_indobert_large_p2_muhammadravi251001` is a English model originally trained by muhammadravi251001. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_indonli_basic_with_indobert_large_p2_muhammadravi251001_en_5.1.4_3.4_1698224046216.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_indonli_basic_with_indobert_large_p2_muhammadravi251001_en_5.1.4_3.4_1698224046216.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_indonli_basic_with_indobert_large_p2_muhammadravi251001","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_indonli_basic_with_indobert_large_p2_muhammadravi251001","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_indonli_basic_with_indobert_large_p2_muhammadravi251001| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/muhammadravi251001/fine-tuned-IndoNLI-Basic-with-indobert-large-p2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_translated_with_indobert_base_uncased_afaji_en.md b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_translated_with_indobert_base_uncased_afaji_en.md new file mode 100644 index 00000000000000..b6bb021fec9193 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_translated_with_indobert_base_uncased_afaji_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English fine_tuned_indonli_translated_with_indobert_base_uncased_afaji BertForSequenceClassification from afaji +author: John Snow Labs +name: fine_tuned_indonli_translated_with_indobert_base_uncased_afaji +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_indonli_translated_with_indobert_base_uncased_afaji` is a English model originally trained by afaji. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_indonli_translated_with_indobert_base_uncased_afaji_en_5.1.4_3.4_1698219456786.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_indonli_translated_with_indobert_base_uncased_afaji_en_5.1.4_3.4_1698219456786.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_indonli_translated_with_indobert_base_uncased_afaji","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_indonli_translated_with_indobert_base_uncased_afaji","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_indonli_translated_with_indobert_base_uncased_afaji| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|413.9 MB| + +## References + +https://huggingface.co/afaji/fine-tuned-IndoNLI-Translated-with-indobert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_translated_with_indobert_base_uncased_muhammadravi251001_en.md b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_translated_with_indobert_base_uncased_muhammadravi251001_en.md new file mode 100644 index 00000000000000..ef47c1fe1b46f2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_translated_with_indobert_base_uncased_muhammadravi251001_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English fine_tuned_indonli_translated_with_indobert_base_uncased_muhammadravi251001 BertForSequenceClassification from muhammadravi251001 +author: John Snow Labs +name: fine_tuned_indonli_translated_with_indobert_base_uncased_muhammadravi251001 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_indonli_translated_with_indobert_base_uncased_muhammadravi251001` is a English model originally trained by muhammadravi251001. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_indonli_translated_with_indobert_base_uncased_muhammadravi251001_en_5.1.4_3.4_1698219097750.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_indonli_translated_with_indobert_base_uncased_muhammadravi251001_en_5.1.4_3.4_1698219097750.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_indonli_translated_with_indobert_base_uncased_muhammadravi251001","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_indonli_translated_with_indobert_base_uncased_muhammadravi251001","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_indonli_translated_with_indobert_base_uncased_muhammadravi251001| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|413.9 MB| + +## References + +https://huggingface.co/muhammadravi251001/fine-tuned-IndoNLI-Translated-with-indobert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_translated_with_indobert_large_p2_en.md b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_translated_with_indobert_large_p2_en.md new file mode 100644 index 00000000000000..37b51526c73bce --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_indonli_translated_with_indobert_large_p2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English fine_tuned_indonli_translated_with_indobert_large_p2 BertForSequenceClassification from afaji +author: John Snow Labs +name: fine_tuned_indonli_translated_with_indobert_large_p2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_indonli_translated_with_indobert_large_p2` is a English model originally trained by afaji. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_indonli_translated_with_indobert_large_p2_en_5.1.4_3.4_1698220492900.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_indonli_translated_with_indobert_large_p2_en_5.1.4_3.4_1698220492900.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_indonli_translated_with_indobert_large_p2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_indonli_translated_with_indobert_large_p2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_indonli_translated_with_indobert_large_p2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/afaji/fine-tuned-IndoNLI-Translated-with-indobert-large-p2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_klue_bert_base_model_11_en.md b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_klue_bert_base_model_11_en.md new file mode 100644 index 00000000000000..978a549659949a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_klue_bert_base_model_11_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English fine_tuned_klue_bert_base_model_11 BertForSequenceClassification from Lanvizu +author: John Snow Labs +name: fine_tuned_klue_bert_base_model_11 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_klue_bert_base_model_11` is a English model originally trained by Lanvizu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_klue_bert_base_model_11_en_5.1.4_3.4_1698192014848.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_klue_bert_base_model_11_en_5.1.4_3.4_1698192014848.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_klue_bert_base_model_11","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_klue_bert_base_model_11","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_klue_bert_base_model_11| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Lanvizu/fine-tuned-klue-bert-base_model_11 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_koreanindonli_kornli_with_bert_base_en.md b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_koreanindonli_kornli_with_bert_base_en.md new file mode 100644 index 00000000000000..c609724838520b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_koreanindonli_kornli_with_bert_base_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English fine_tuned_koreanindonli_kornli_with_bert_base BertForSequenceClassification from muhammadravi251001 +author: John Snow Labs +name: fine_tuned_koreanindonli_kornli_with_bert_base +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_koreanindonli_kornli_with_bert_base` is a English model originally trained by muhammadravi251001. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_koreanindonli_kornli_with_bert_base_en_5.1.4_3.4_1698245173848.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_koreanindonli_kornli_with_bert_base_en_5.1.4_3.4_1698245173848.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_koreanindonli_kornli_with_bert_base","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_koreanindonli_kornli_with_bert_base","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_koreanindonli_kornli_with_bert_base| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.6 MB| + +## References + +https://huggingface.co/muhammadravi251001/fine-tuned-KoreanIndoNLI-KorNLI-with-bert-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_koreanindonli_kornli_with_bert_kor_base_en.md b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_koreanindonli_kornli_with_bert_kor_base_en.md new file mode 100644 index 00000000000000..afb80453f32e98 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-fine_tuned_koreanindonli_kornli_with_bert_kor_base_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English fine_tuned_koreanindonli_kornli_with_bert_kor_base BertForSequenceClassification from muhammadravi251001 +author: John Snow Labs +name: fine_tuned_koreanindonli_kornli_with_bert_kor_base +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tuned_koreanindonli_kornli_with_bert_kor_base` is a English model originally trained by muhammadravi251001. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tuned_koreanindonli_kornli_with_bert_kor_base_en_5.1.4_3.4_1698228339319.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tuned_koreanindonli_kornli_with_bert_kor_base_en_5.1.4_3.4_1698228339319.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_koreanindonli_kornli_with_bert_kor_base","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fine_tuned_koreanindonli_kornli_with_bert_kor_base","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tuned_koreanindonli_kornli_with_bert_kor_base| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|443.4 MB| + +## References + +https://huggingface.co/muhammadravi251001/fine-tuned-KoreanIndoNLI-KorNLI-with-bert-kor-base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-finetune_bert_base_cased_en.md b/docs/_posts/ahmedlone127/2023-10-25-finetune_bert_base_cased_en.md new file mode 100644 index 00000000000000..fb3ed38e59a749 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-finetune_bert_base_cased_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English finetune_bert_base_cased BertForSequenceClassification from LIALLIES +author: John Snow Labs +name: finetune_bert_base_cased +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetune_bert_base_cased` is a English model originally trained by LIALLIES. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetune_bert_base_cased_en_5.1.4_3.4_1698211012078.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetune_bert_base_cased_en_5.1.4_3.4_1698211012078.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("finetune_bert_base_cased","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finetune_bert_base_cased","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetune_bert_base_cased| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/LIALLIES/finetune-bert-base-cased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-finetuned_bert_base_uncased_minoosh_en.md b/docs/_posts/ahmedlone127/2023-10-25-finetuned_bert_base_uncased_minoosh_en.md new file mode 100644 index 00000000000000..f4bb5f1b7b37cf --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-finetuned_bert_base_uncased_minoosh_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English finetuned_bert_base_uncased_minoosh BertForSequenceClassification from minoosh +author: John Snow Labs +name: finetuned_bert_base_uncased_minoosh +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_bert_base_uncased_minoosh` is a English model originally trained by minoosh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bert_base_uncased_minoosh_en_5.1.4_3.4_1698199009303.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bert_base_uncased_minoosh_en_5.1.4_3.4_1698199009303.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("finetuned_bert_base_uncased_minoosh","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finetuned_bert_base_uncased_minoosh","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_bert_base_uncased_minoosh| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/minoosh/finetuned_bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-finetuned_bert_mrpc_ndugar_en.md b/docs/_posts/ahmedlone127/2023-10-25-finetuned_bert_mrpc_ndugar_en.md new file mode 100644 index 00000000000000..92a237b46c2e5b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-finetuned_bert_mrpc_ndugar_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English finetuned_bert_mrpc_ndugar BertForSequenceClassification from NDugar +author: John Snow Labs +name: finetuned_bert_mrpc_ndugar +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_bert_mrpc_ndugar` is a English model originally trained by NDugar. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bert_mrpc_ndugar_en_5.1.4_3.4_1698226789566.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bert_mrpc_ndugar_en_5.1.4_3.4_1698226789566.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("finetuned_bert_mrpc_ndugar","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finetuned_bert_mrpc_ndugar","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_bert_mrpc_ndugar| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/NDugar/finetuned-bert-mrpc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-finetuned_bert_yelp_v1_en.md b/docs/_posts/ahmedlone127/2023-10-25-finetuned_bert_yelp_v1_en.md new file mode 100644 index 00000000000000..cbed96694bf205 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-finetuned_bert_yelp_v1_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English finetuned_bert_yelp_v1 BertForSequenceClassification from ranraj99 +author: John Snow Labs +name: finetuned_bert_yelp_v1 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_bert_yelp_v1` is a English model originally trained by ranraj99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_bert_yelp_v1_en_5.1.4_3.4_1698269477838.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_bert_yelp_v1_en_5.1.4_3.4_1698269477838.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("finetuned_bert_yelp_v1","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finetuned_bert_yelp_v1","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_bert_yelp_v1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/ranraj99/finetuned_bert_yelp_v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-finetuned_iitp_pdt_review_additionalpretrained_bert_base_cased_en.md b/docs/_posts/ahmedlone127/2023-10-25-finetuned_iitp_pdt_review_additionalpretrained_bert_base_cased_en.md new file mode 100644 index 00000000000000..b451842c232238 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-finetuned_iitp_pdt_review_additionalpretrained_bert_base_cased_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English finetuned_iitp_pdt_review_additionalpretrained_bert_base_cased BertForSequenceClassification from aditeyabaral +author: John Snow Labs +name: finetuned_iitp_pdt_review_additionalpretrained_bert_base_cased +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_iitp_pdt_review_additionalpretrained_bert_base_cased` is a English model originally trained by aditeyabaral. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_iitp_pdt_review_additionalpretrained_bert_base_cased_en_5.1.4_3.4_1698270716179.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_iitp_pdt_review_additionalpretrained_bert_base_cased_en_5.1.4_3.4_1698270716179.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("finetuned_iitp_pdt_review_additionalpretrained_bert_base_cased","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finetuned_iitp_pdt_review_additionalpretrained_bert_base_cased","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_iitp_pdt_review_additionalpretrained_bert_base_cased| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/aditeyabaral/finetuned-iitp_pdt_review-additionalpretrained-bert-base-cased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-finetuned_iitp_pdt_review_bert_hinglish_big_en.md b/docs/_posts/ahmedlone127/2023-10-25-finetuned_iitp_pdt_review_bert_hinglish_big_en.md new file mode 100644 index 00000000000000..08d1b2ffdb65ec --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-finetuned_iitp_pdt_review_bert_hinglish_big_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English finetuned_iitp_pdt_review_bert_hinglish_big BertForSequenceClassification from aditeyabaral +author: John Snow Labs +name: finetuned_iitp_pdt_review_bert_hinglish_big +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_iitp_pdt_review_bert_hinglish_big` is a English model originally trained by aditeyabaral. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_iitp_pdt_review_bert_hinglish_big_en_5.1.4_3.4_1698271343226.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_iitp_pdt_review_bert_hinglish_big_en_5.1.4_3.4_1698271343226.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("finetuned_iitp_pdt_review_bert_hinglish_big","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finetuned_iitp_pdt_review_bert_hinglish_big","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_iitp_pdt_review_bert_hinglish_big| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|251.2 MB| + +## References + +https://huggingface.co/aditeyabaral/finetuned-iitp_pdt_review-bert-hinglish-big \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-finetuned_iitp_pdt_review_bert_hinglish_small_en.md b/docs/_posts/ahmedlone127/2023-10-25-finetuned_iitp_pdt_review_bert_hinglish_small_en.md new file mode 100644 index 00000000000000..91b1f3dc23983b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-finetuned_iitp_pdt_review_bert_hinglish_small_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English finetuned_iitp_pdt_review_bert_hinglish_small BertForSequenceClassification from aditeyabaral +author: John Snow Labs +name: finetuned_iitp_pdt_review_bert_hinglish_small +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_iitp_pdt_review_bert_hinglish_small` is a English model originally trained by aditeyabaral. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_iitp_pdt_review_bert_hinglish_small_en_5.1.4_3.4_1698272312849.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_iitp_pdt_review_bert_hinglish_small_en_5.1.4_3.4_1698272312849.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("finetuned_iitp_pdt_review_bert_hinglish_small","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finetuned_iitp_pdt_review_bert_hinglish_small","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_iitp_pdt_review_bert_hinglish_small| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|251.2 MB| + +## References + +https://huggingface.co/aditeyabaral/finetuned-iitp_pdt_review-bert-hinglish-small \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-finetuned_iitpmovie_additionalpretrained_bert_base_cased_en.md b/docs/_posts/ahmedlone127/2023-10-25-finetuned_iitpmovie_additionalpretrained_bert_base_cased_en.md new file mode 100644 index 00000000000000..e44718c50789b3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-finetuned_iitpmovie_additionalpretrained_bert_base_cased_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English finetuned_iitpmovie_additionalpretrained_bert_base_cased BertForSequenceClassification from aditeyabaral +author: John Snow Labs +name: finetuned_iitpmovie_additionalpretrained_bert_base_cased +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_iitpmovie_additionalpretrained_bert_base_cased` is a English model originally trained by aditeyabaral. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_iitpmovie_additionalpretrained_bert_base_cased_en_5.1.4_3.4_1698273021943.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_iitpmovie_additionalpretrained_bert_base_cased_en_5.1.4_3.4_1698273021943.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("finetuned_iitpmovie_additionalpretrained_bert_base_cased","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finetuned_iitpmovie_additionalpretrained_bert_base_cased","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_iitpmovie_additionalpretrained_bert_base_cased| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/aditeyabaral/finetuned-iitpmovie-additionalpretrained-bert-base-cased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-finetuned_sail2017_additionalpretrained_bert_base_cased_en.md b/docs/_posts/ahmedlone127/2023-10-25-finetuned_sail2017_additionalpretrained_bert_base_cased_en.md new file mode 100644 index 00000000000000..2f49078b049b8c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-finetuned_sail2017_additionalpretrained_bert_base_cased_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English finetuned_sail2017_additionalpretrained_bert_base_cased BertForSequenceClassification from aditeyabaral +author: John Snow Labs +name: finetuned_sail2017_additionalpretrained_bert_base_cased +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_sail2017_additionalpretrained_bert_base_cased` is a English model originally trained by aditeyabaral. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_sail2017_additionalpretrained_bert_base_cased_en_5.1.4_3.4_1698273843099.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_sail2017_additionalpretrained_bert_base_cased_en_5.1.4_3.4_1698273843099.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("finetuned_sail2017_additionalpretrained_bert_base_cased","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finetuned_sail2017_additionalpretrained_bert_base_cased","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_sail2017_additionalpretrained_bert_base_cased| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/aditeyabaral/finetuned-sail2017-additionalpretrained-bert-base-cased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-finetuned_sail2017_bert_base_cased_en.md b/docs/_posts/ahmedlone127/2023-10-25-finetuned_sail2017_bert_base_cased_en.md new file mode 100644 index 00000000000000..ac2f9a90cdae01 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-finetuned_sail2017_bert_base_cased_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English finetuned_sail2017_bert_base_cased BertForSequenceClassification from aditeyabaral +author: John Snow Labs +name: finetuned_sail2017_bert_base_cased +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_sail2017_bert_base_cased` is a English model originally trained by aditeyabaral. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_sail2017_bert_base_cased_en_5.1.4_3.4_1698274459616.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_sail2017_bert_base_cased_en_5.1.4_3.4_1698274459616.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("finetuned_sail2017_bert_base_cased","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finetuned_sail2017_bert_base_cased","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_sail2017_bert_base_cased| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/aditeyabaral/finetuned-sail2017-bert-base-cased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-finetuned_sc_indobert_on_indonli_basic_train_en.md b/docs/_posts/ahmedlone127/2023-10-25-finetuned_sc_indobert_on_indonli_basic_train_en.md new file mode 100644 index 00000000000000..beb9316c37f89e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-finetuned_sc_indobert_on_indonli_basic_train_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English finetuned_sc_indobert_on_indonli_basic_train BertForSequenceClassification from muhammadravi251001 +author: John Snow Labs +name: finetuned_sc_indobert_on_indonli_basic_train +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetuned_sc_indobert_on_indonli_basic_train` is a English model originally trained by muhammadravi251001. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetuned_sc_indobert_on_indonli_basic_train_en_5.1.4_3.4_1698216396244.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetuned_sc_indobert_on_indonli_basic_train_en_5.1.4_3.4_1698216396244.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("finetuned_sc_indobert_on_indonli_basic_train","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finetuned_sc_indobert_on_indonli_basic_train","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetuned_sc_indobert_on_indonli_basic_train| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|413.9 MB| + +## References + +https://huggingface.co/muhammadravi251001/finetuned-SC-indobert-on-indonli_basic-train \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-finetunedfinbert_model_en.md b/docs/_posts/ahmedlone127/2023-10-25-finetunedfinbert_model_en.md new file mode 100644 index 00000000000000..ba61880a841e9f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-finetunedfinbert_model_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English finetunedfinbert_model BertForSequenceClassification from Himanshusingh +author: John Snow Labs +name: finetunedfinbert_model +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finetunedfinbert_model` is a English model originally trained by Himanshusingh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finetunedfinbert_model_en_5.1.4_3.4_1698215223380.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finetunedfinbert_model_en_5.1.4_3.4_1698215223380.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("finetunedfinbert_model","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finetunedfinbert_model","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finetunedfinbert_model| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Himanshusingh/finetunedfinbert-model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-gbert_base_ft_edu_redux_de.md b/docs/_posts/ahmedlone127/2023-10-25-gbert_base_ft_edu_redux_de.md new file mode 100644 index 00000000000000..d5dab38447a7e4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-gbert_base_ft_edu_redux_de.md @@ -0,0 +1,97 @@ +--- +layout: model +title: German gbert_base_ft_edu_redux BertForSequenceClassification from gonzpen +author: John Snow Labs +name: gbert_base_ft_edu_redux +date: 2023-10-25 +tags: [bert, de, open_source, sequence_classification, onnx] +task: Text Classification +language: de +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gbert_base_ft_edu_redux` is a German model originally trained by gonzpen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gbert_base_ft_edu_redux_de_5.1.4_3.4_1698248491071.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gbert_base_ft_edu_redux_de_5.1.4_3.4_1698248491071.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("gbert_base_ft_edu_redux","de")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("gbert_base_ft_edu_redux","de") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gbert_base_ft_edu_redux| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|de| +|Size:|412.0 MB| + +## References + +https://huggingface.co/gonzpen/gbert-base-ft-edu-redux \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-gbert_base_germeval21_toxic_en.md b/docs/_posts/ahmedlone127/2023-10-25-gbert_base_germeval21_toxic_en.md new file mode 100644 index 00000000000000..9466a85bfc6b69 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-gbert_base_germeval21_toxic_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English gbert_base_germeval21_toxic BertForSequenceClassification from airKlizz +author: John Snow Labs +name: gbert_base_germeval21_toxic +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gbert_base_germeval21_toxic` is a English model originally trained by airKlizz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gbert_base_germeval21_toxic_en_5.1.4_3.4_1698277581036.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gbert_base_germeval21_toxic_en_5.1.4_3.4_1698277581036.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("gbert_base_germeval21_toxic","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("gbert_base_germeval21_toxic","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gbert_base_germeval21_toxic| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|412.0 MB| + +## References + +https://huggingface.co/airKlizz/gbert-base-germeval21-toxic \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-gbert_base_germeval21_toxic_with_data_augmentation_en.md b/docs/_posts/ahmedlone127/2023-10-25-gbert_base_germeval21_toxic_with_data_augmentation_en.md new file mode 100644 index 00000000000000..ef757c1e4b6f16 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-gbert_base_germeval21_toxic_with_data_augmentation_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English gbert_base_germeval21_toxic_with_data_augmentation BertForSequenceClassification from airKlizz +author: John Snow Labs +name: gbert_base_germeval21_toxic_with_data_augmentation +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gbert_base_germeval21_toxic_with_data_augmentation` is a English model originally trained by airKlizz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gbert_base_germeval21_toxic_with_data_augmentation_en_5.1.4_3.4_1698276924848.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gbert_base_germeval21_toxic_with_data_augmentation_en_5.1.4_3.4_1698276924848.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("gbert_base_germeval21_toxic_with_data_augmentation","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("gbert_base_germeval21_toxic_with_data_augmentation","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gbert_base_germeval21_toxic_with_data_augmentation| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|412.0 MB| + +## References + +https://huggingface.co/airKlizz/gbert-base-germeval21-toxic-with-data-augmentation \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-gbert_large_ft_edu_redux_de.md b/docs/_posts/ahmedlone127/2023-10-25-gbert_large_ft_edu_redux_de.md new file mode 100644 index 00000000000000..47a9010f53d233 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-gbert_large_ft_edu_redux_de.md @@ -0,0 +1,97 @@ +--- +layout: model +title: German gbert_large_ft_edu_redux BertForSequenceClassification from gonzpen +author: John Snow Labs +name: gbert_large_ft_edu_redux +date: 2023-10-25 +tags: [bert, de, open_source, sequence_classification, onnx] +task: Text Classification +language: de +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gbert_large_ft_edu_redux` is a German model originally trained by gonzpen. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gbert_large_ft_edu_redux_de_5.1.4_3.4_1698251634199.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gbert_large_ft_edu_redux_de_5.1.4_3.4_1698251634199.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("gbert_large_ft_edu_redux","de")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("gbert_large_ft_edu_redux","de") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gbert_large_ft_edu_redux| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|de| +|Size:|1.3 GB| + +## References + +https://huggingface.co/gonzpen/gbert-large-ft-edu-redux \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-german_tweetstance_bert_uncased_russiaukrainewar_de.md b/docs/_posts/ahmedlone127/2023-10-25-german_tweetstance_bert_uncased_russiaukrainewar_de.md new file mode 100644 index 00000000000000..9d22e58d14280d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-german_tweetstance_bert_uncased_russiaukrainewar_de.md @@ -0,0 +1,97 @@ +--- +layout: model +title: German german_tweetstance_bert_uncased_russiaukrainewar BertForSequenceClassification from joh-ga +author: John Snow Labs +name: german_tweetstance_bert_uncased_russiaukrainewar +date: 2023-10-25 +tags: [bert, de, open_source, sequence_classification, onnx] +task: Text Classification +language: de +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`german_tweetstance_bert_uncased_russiaukrainewar` is a German model originally trained by joh-ga. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/german_tweetstance_bert_uncased_russiaukrainewar_de_5.1.4_3.4_1698263251275.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/german_tweetstance_bert_uncased_russiaukrainewar_de_5.1.4_3.4_1698263251275.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("german_tweetstance_bert_uncased_russiaukrainewar","de")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("german_tweetstance_bert_uncased_russiaukrainewar","de") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|german_tweetstance_bert_uncased_russiaukrainewar| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|de| +|Size:|412.1 MB| + +## References + +https://huggingface.co/joh-ga/german-tweetstance-bert-uncased-russiaukrainewar \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-gikubu_bert_base_en.md b/docs/_posts/ahmedlone127/2023-10-25-gikubu_bert_base_en.md new file mode 100644 index 00000000000000..086a199324709a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-gikubu_bert_base_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English gikubu_bert_base BertForSequenceClassification from Gikubu +author: John Snow Labs +name: gikubu_bert_base +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`gikubu_bert_base` is a English model originally trained by Gikubu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/gikubu_bert_base_en_5.1.4_3.4_1698201580816.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/gikubu_bert_base_en_5.1.4_3.4_1698201580816.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("gikubu_bert_base","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("gikubu_bert_base","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|gikubu_bert_base| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Gikubu/Gikubu_bert_base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_0_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_0_en.md new file mode 100644 index 00000000000000..86cecc2177ed20 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_0_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_0 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_0 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_0` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_0_en_5.1.4_3.4_1698214940352.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_0_en_5.1.4_3.4_1698214940352.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_0","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_0","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_0| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_10_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_10_en.md new file mode 100644 index 00000000000000..daf4e73e0800a9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_10_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_10 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_10 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_10` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_10_en_5.1.4_3.4_1698215468969.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_10_en_5.1.4_3.4_1698215468969.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_10","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_10","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_10| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_11_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_11_en.md new file mode 100644 index 00000000000000..a80cb2d6ddec10 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_11_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_11 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_11 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_11` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_11_en_5.1.4_3.4_1698216069006.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_11_en_5.1.4_3.4_1698216069006.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_11","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_11","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_11| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-11 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_12_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_12_en.md new file mode 100644 index 00000000000000..d407570ebbe125 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_12_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_12 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_12 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_12` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_12_en_5.1.4_3.4_1698216256946.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_12_en_5.1.4_3.4_1698216256946.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_12","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_12","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_12| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-12 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_13_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_13_en.md new file mode 100644 index 00000000000000..bd26d5f765651e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_13_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_13 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_13 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_13` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_13_en_5.1.4_3.4_1698216806137.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_13_en_5.1.4_3.4_1698216806137.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_13","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_13","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_13| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-13 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_14_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_14_en.md new file mode 100644 index 00000000000000..926c43f8080c6f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_14_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_14 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_14 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_14` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_14_en_5.1.4_3.4_1698216461612.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_14_en_5.1.4_3.4_1698216461612.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_14","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_14","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_14| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-14 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_15_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_15_en.md new file mode 100644 index 00000000000000..eff3836d2463d5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_15_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_15 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_15 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_15` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_15_en_5.1.4_3.4_1698218006990.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_15_en_5.1.4_3.4_1698218006990.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_15","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_15","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_15| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-15 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_16_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_16_en.md new file mode 100644 index 00000000000000..5e2f6baa8ce8e4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_16_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_16 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_16 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_16` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_16_en_5.1.4_3.4_1698217161066.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_16_en_5.1.4_3.4_1698217161066.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_16","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_16","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_16| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-16 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_17_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_17_en.md new file mode 100644 index 00000000000000..66b75e337a67e8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_17_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_17 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_17 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_17` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_17_en_5.1.4_3.4_1698216972783.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_17_en_5.1.4_3.4_1698216972783.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_17","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_17","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_17| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-17 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_18_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_18_en.md new file mode 100644 index 00000000000000..24ed3f394e1b7a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_18_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_18 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_18 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_18` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_18_en_5.1.4_3.4_1698216649878.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_18_en_5.1.4_3.4_1698216649878.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_18","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_18","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_18| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-18 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_19_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_19_en.md new file mode 100644 index 00000000000000..eff358c5fb7547 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_19_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_19 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_19 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_19` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_19_en_5.1.4_3.4_1698218217176.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_19_en_5.1.4_3.4_1698218217176.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_19","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_19","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_19| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-19 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_1_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_1_en.md new file mode 100644 index 00000000000000..8cdd2e603280e1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_1_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_1 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_1 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_1` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_1_en_5.1.4_3.4_1698214773723.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_1_en_5.1.4_3.4_1698214773723.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_1","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_1","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_20_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_20_en.md new file mode 100644 index 00000000000000..ee8febc77f995a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_20_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_20 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_20 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_20` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_20_en_5.1.4_3.4_1698217370941.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_20_en_5.1.4_3.4_1698217370941.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_20","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_20","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_20| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-20 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_21_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_21_en.md new file mode 100644 index 00000000000000..f3a087bdcfa5b5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_21_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_21 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_21 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_21` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_21_en_5.1.4_3.4_1698217595519.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_21_en_5.1.4_3.4_1698217595519.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_21","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_21","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_21| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-21 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_22_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_22_en.md new file mode 100644 index 00000000000000..b40c94252c46a3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_22_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_22 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_22 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_22` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_22_en_5.1.4_3.4_1698217792710.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_22_en_5.1.4_3.4_1698217792710.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_22","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_22","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_22| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-22 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_23_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_23_en.md new file mode 100644 index 00000000000000..10f7b5ba369f76 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_23_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_23 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_23 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_23` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_23_en_5.1.4_3.4_1698222310863.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_23_en_5.1.4_3.4_1698222310863.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_23","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_23","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_23| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-23 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_24_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_24_en.md new file mode 100644 index 00000000000000..80f0e899b951eb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_24_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_24 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_24 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_24` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_24_en_5.1.4_3.4_1698222516029.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_24_en_5.1.4_3.4_1698222516029.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_24","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_24","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_24| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-24 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_25_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_25_en.md new file mode 100644 index 00000000000000..624ae4afe9d9ca --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_25_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_25 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_25 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_25` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_25_en_5.1.4_3.4_1698219051243.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_25_en_5.1.4_3.4_1698219051243.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_25","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_25","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_25| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-25 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_26_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_26_en.md new file mode 100644 index 00000000000000..5ad2b7a3ce6c60 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_26_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_26 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_26 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_26` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_26_en_5.1.4_3.4_1698219644965.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_26_en_5.1.4_3.4_1698219644965.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_26","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_26","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_26| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-26 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_27_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_27_en.md new file mode 100644 index 00000000000000..67b503f850af62 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_27_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_27 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_27 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_27` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_27_en_5.1.4_3.4_1698218599491.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_27_en_5.1.4_3.4_1698218599491.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_27","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_27","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_27| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-27 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_28_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_28_en.md new file mode 100644 index 00000000000000..add184fe24151e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_28_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_28 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_28 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_28` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_28_en_5.1.4_3.4_1698218829163.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_28_en_5.1.4_3.4_1698218829163.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_28","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_28","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_28| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-28 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_29_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_29_en.md new file mode 100644 index 00000000000000..5be4e0b72efe6b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_29_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_29 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_29 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_29` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_29_en_5.1.4_3.4_1698261490840.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_29_en_5.1.4_3.4_1698261490840.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_29","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_29","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_29| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-29 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_2_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_2_en.md new file mode 100644 index 00000000000000..a4cf05ad5caaab --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_2 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_2` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_2_en_5.1.4_3.4_1698214164302.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_2_en_5.1.4_3.4_1698214164302.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_30_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_30_en.md new file mode 100644 index 00000000000000..6ddedc444a2eea --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_30_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_30 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_30 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_30` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_30_en_5.1.4_3.4_1698219245865.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_30_en_5.1.4_3.4_1698219245865.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_30","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_30","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_30| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-30 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_31_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_31_en.md new file mode 100644 index 00000000000000..9164a916b483c0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_31_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_31 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_31 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_31` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_31_en_5.1.4_3.4_1698218399794.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_31_en_5.1.4_3.4_1698218399794.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_31","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_31","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_31| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-31 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_32_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_32_en.md new file mode 100644 index 00000000000000..64ea0587bf2874 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_32_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_32 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_32 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_32` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_32_en_5.1.4_3.4_1698219435732.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_32_en_5.1.4_3.4_1698219435732.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_32","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_32","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_32| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-32 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_33_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_33_en.md new file mode 100644 index 00000000000000..ee7679c3eca54d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_33_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_33 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_33 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_33` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_33_en_5.1.4_3.4_1698219845008.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_33_en_5.1.4_3.4_1698219845008.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_33","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_33","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_33| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-33 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_34_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_34_en.md new file mode 100644 index 00000000000000..d1e5636311de44 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_34_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_34 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_34 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_34` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_34_en_5.1.4_3.4_1698220231904.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_34_en_5.1.4_3.4_1698220231904.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_34","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_34","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_34| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-34 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_35_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_35_en.md new file mode 100644 index 00000000000000..da0bd10c0c1f63 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_35_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_35 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_35 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_35` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_35_en_5.1.4_3.4_1698220033273.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_35_en_5.1.4_3.4_1698220033273.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_35","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_35","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_35| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-35 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_36_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_36_en.md new file mode 100644 index 00000000000000..cfcef8587f4844 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_36_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_36 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_36 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_36` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_36_en_5.1.4_3.4_1698220575602.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_36_en_5.1.4_3.4_1698220575602.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_36","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_36","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_36| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-36 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_37_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_37_en.md new file mode 100644 index 00000000000000..02cdb814d6ab38 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_37_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_37 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_37 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_37` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_37_en_5.1.4_3.4_1698220419732.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_37_en_5.1.4_3.4_1698220419732.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_37","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_37","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_37| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-37 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_38_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_38_en.md new file mode 100644 index 00000000000000..b82bfd6d3288aa --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_38_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_38 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_38 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_38` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_38_en_5.1.4_3.4_1698220977338.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_38_en_5.1.4_3.4_1698220977338.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_38","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_38","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_38| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-38 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_39_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_39_en.md new file mode 100644 index 00000000000000..76d2b0e394ff87 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_39_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_39 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_39 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_39` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_39_en_5.1.4_3.4_1698221378949.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_39_en_5.1.4_3.4_1698221378949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_39","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_39","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_39| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-39 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_3_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_3_en.md new file mode 100644 index 00000000000000..8150098741b8bf --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_3_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_3 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_3 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_3` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_3_en_5.1.4_3.4_1698215297155.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_3_en_5.1.4_3.4_1698215297155.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_3","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_3","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_3| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_40_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_40_en.md new file mode 100644 index 00000000000000..cb7ef6fdf253d1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_40_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_40 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_40 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_40` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_40_en_5.1.4_3.4_1698221167152.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_40_en_5.1.4_3.4_1698221167152.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_40","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_40","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_40| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-40 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_41_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_41_en.md new file mode 100644 index 00000000000000..98b5a18461d1ed --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_41_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_41 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_41 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_41` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_41_en_5.1.4_3.4_1698220788822.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_41_en_5.1.4_3.4_1698220788822.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_41","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_41","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_41| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-41 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_42_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_42_en.md new file mode 100644 index 00000000000000..208db8035d1ad9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_42_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_42 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_42 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_42` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_42_en_5.1.4_3.4_1698221947943.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_42_en_5.1.4_3.4_1698221947943.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_42","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_42","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_42| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-42 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_43_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_43_en.md new file mode 100644 index 00000000000000..98b58fc5562163 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_43_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_43 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_43 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_43` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_43_en_5.1.4_3.4_1698221771690.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_43_en_5.1.4_3.4_1698221771690.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_43","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_43","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_43| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-43 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_44_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_44_en.md new file mode 100644 index 00000000000000..86685d30bbac38 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_44_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_44 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_44 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_44` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_44_en_5.1.4_3.4_1698222126299.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_44_en_5.1.4_3.4_1698222126299.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_44","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_44","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_44| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-44 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_45_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_45_en.md new file mode 100644 index 00000000000000..9e80699e8a0ae9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_45_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_45 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_45 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_45` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_45_en_5.1.4_3.4_1698221572355.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_45_en_5.1.4_3.4_1698221572355.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_45","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_45","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_45| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-45 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_46_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_46_en.md new file mode 100644 index 00000000000000..4a5551ef179908 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_46_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_46 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_46 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_46` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_46_en_5.1.4_3.4_1698222695220.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_46_en_5.1.4_3.4_1698222695220.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_46","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_46","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_46| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-46 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_47_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_47_en.md new file mode 100644 index 00000000000000..abe8336f4ea9a2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_47_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_47 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_47 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_47` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_47_en_5.1.4_3.4_1698222867221.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_47_en_5.1.4_3.4_1698222867221.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_47","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_47","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_47| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-47 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_48_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_48_en.md new file mode 100644 index 00000000000000..abce1cdf1dcc68 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_48_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_48 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_48 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_48` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_48_en_5.1.4_3.4_1698225719514.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_48_en_5.1.4_3.4_1698225719514.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_48","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_48","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_48| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-48 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_49_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_49_en.md new file mode 100644 index 00000000000000..9f0c57140f6d0d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_49_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_49 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_49 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_49` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_49_en_5.1.4_3.4_1698229026818.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_49_en_5.1.4_3.4_1698229026818.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_49","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_49","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_49| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-49 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_4_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_4_en.md new file mode 100644 index 00000000000000..9a84a8d43abe46 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_4_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_4 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_4 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_4` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_4_en_5.1.4_3.4_1698213968576.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_4_en_5.1.4_3.4_1698213968576.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_4","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_4","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_4| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_50_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_50_en.md new file mode 100644 index 00000000000000..cd94e000f51da6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_50_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_50 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_50 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_50` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_50_en_5.1.4_3.4_1698231600698.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_50_en_5.1.4_3.4_1698231600698.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_50","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_50","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_50| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-50 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_51_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_51_en.md new file mode 100644 index 00000000000000..18bc0c70d31135 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_51_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_51 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_51 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_51` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_51_en_5.1.4_3.4_1698227400253.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_51_en_5.1.4_3.4_1698227400253.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_51","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_51","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_51| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-51 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_52_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_52_en.md new file mode 100644 index 00000000000000..0213934506a26a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_52_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_52 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_52 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_52` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_52_en_5.1.4_3.4_1698224786799.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_52_en_5.1.4_3.4_1698224786799.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_52","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_52","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_52| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-52 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_53_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_53_en.md new file mode 100644 index 00000000000000..71f33047ff8ca0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_53_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_53 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_53 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_53` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_53_en_5.1.4_3.4_1698225000509.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_53_en_5.1.4_3.4_1698225000509.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_53","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_53","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_53| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-53 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_54_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_54_en.md new file mode 100644 index 00000000000000..2390033ee09458 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_54_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_54 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_54 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_54` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_54_en_5.1.4_3.4_1698230803166.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_54_en_5.1.4_3.4_1698230803166.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_54","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_54","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_54| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-54 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_55_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_55_en.md new file mode 100644 index 00000000000000..d273e6a62e91d0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_55_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_55 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_55 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_55` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_55_en_5.1.4_3.4_1698229934190.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_55_en_5.1.4_3.4_1698229934190.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_55","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_55","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_55| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-55 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_56_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_56_en.md new file mode 100644 index 00000000000000..3cca9930f87549 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_56_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_56 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_56 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_56` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_56_en_5.1.4_3.4_1698226620229.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_56_en_5.1.4_3.4_1698226620229.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_56","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_56","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_56| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-56 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_57_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_57_en.md new file mode 100644 index 00000000000000..6333ebd3b81807 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_57_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_57 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_57 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_57` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_57_en_5.1.4_3.4_1698228126156.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_57_en_5.1.4_3.4_1698228126156.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_57","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_57","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_57| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-57 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_58_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_58_en.md new file mode 100644 index 00000000000000..d6d1a9450b8f47 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_58_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_58 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_58 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_58` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_58_en_5.1.4_3.4_1698235996382.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_58_en_5.1.4_3.4_1698235996382.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_58","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_58","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_58| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-58 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_59_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_59_en.md new file mode 100644 index 00000000000000..0fa6ae8ccc1213 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_59_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_59 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_59 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_59` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_59_en_5.1.4_3.4_1698236948806.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_59_en_5.1.4_3.4_1698236948806.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_59","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_59","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_59| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-59 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_5_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_5_en.md new file mode 100644 index 00000000000000..52dd40bcc4dd5c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_5_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_5 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_5 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_5` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_5_en_5.1.4_3.4_1698214559777.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_5_en_5.1.4_3.4_1698214559777.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_5","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_5","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_5| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_60_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_60_en.md new file mode 100644 index 00000000000000..8cbdb3d1be1f56 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_60_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_60 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_60 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_60` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_60_en_5.1.4_3.4_1698224363748.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_60_en_5.1.4_3.4_1698224363748.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_60","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_60","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_60| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-60 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_61_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_61_en.md new file mode 100644 index 00000000000000..1b7d5299d6c7dd --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_61_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_61 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_61 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_61` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_61_en_5.1.4_3.4_1698237883855.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_61_en_5.1.4_3.4_1698237883855.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_61","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_61","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_61| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-61 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_62_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_62_en.md new file mode 100644 index 00000000000000..6e1ab25b09c2e1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_62_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_62 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_62 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_62` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_62_en_5.1.4_3.4_1698239026933.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_62_en_5.1.4_3.4_1698239026933.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_62","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_62","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_62| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-62 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_63_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_63_en.md new file mode 100644 index 00000000000000..37e917d2144fad --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_63_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_63 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_63 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_63` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_63_en_5.1.4_3.4_1698224150303.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_63_en_5.1.4_3.4_1698224150303.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_63","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_63","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_63| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-63 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_64_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_64_en.md new file mode 100644 index 00000000000000..fc8b6cad2d4af7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_64_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_64 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_64 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_64` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_64_en_5.1.4_3.4_1698232386985.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_64_en_5.1.4_3.4_1698232386985.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_64","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_64","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_64| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-64 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_65_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_65_en.md new file mode 100644 index 00000000000000..3c511abdf76e74 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_65_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_65 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_65 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_65` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_65_en_5.1.4_3.4_1698234886083.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_65_en_5.1.4_3.4_1698234886083.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_65","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_65","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_65| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-65 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_66_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_66_en.md new file mode 100644 index 00000000000000..58193b59a8aa0d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_66_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_66 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_66 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_66` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_66_en_5.1.4_3.4_1698239876018.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_66_en_5.1.4_3.4_1698239876018.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_66","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_66","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_66| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-66 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_67_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_67_en.md new file mode 100644 index 00000000000000..fa12338d9dd42a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_67_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_67 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_67 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_67` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_67_en_5.1.4_3.4_1698233984646.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_67_en_5.1.4_3.4_1698233984646.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_67","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_67","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_67| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-67 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_68_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_68_en.md new file mode 100644 index 00000000000000..a6dddfecc8d91c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_68_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_68 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_68 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_68` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_68_en_5.1.4_3.4_1698223587499.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_68_en_5.1.4_3.4_1698223587499.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_68","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_68","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_68| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-68 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_69_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_69_en.md new file mode 100644 index 00000000000000..124ef297147464 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_69_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_69 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_69 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_69` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_69_en_5.1.4_3.4_1698224583571.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_69_en_5.1.4_3.4_1698224583571.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_69","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_69","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_69| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-69 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_6_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_6_en.md new file mode 100644 index 00000000000000..08d563cef1d210 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_6_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_6 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_6 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_6` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_6_en_5.1.4_3.4_1698214361592.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_6_en_5.1.4_3.4_1698214361592.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_6","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_6","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_6| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_70_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_70_en.md new file mode 100644 index 00000000000000..b609c5b69696b2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_70_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_70 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_70 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_70` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_70_en_5.1.4_3.4_1698233231183.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_70_en_5.1.4_3.4_1698233231183.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_70","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_70","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_70| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-70 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_71_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_71_en.md new file mode 100644 index 00000000000000..9a6ee5a84ab843 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_71_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_71 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_71 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_71` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_71_en_5.1.4_3.4_1698223045460.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_71_en_5.1.4_3.4_1698223045460.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_71","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_71","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_71| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-71 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_72_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_72_en.md new file mode 100644 index 00000000000000..8e8a4e73a26404 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_72_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_72 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_72 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_72` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_72_en_5.1.4_3.4_1698223744727.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_72_en_5.1.4_3.4_1698223744727.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_72","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_72","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_72| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-72 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_73_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_73_en.md new file mode 100644 index 00000000000000..d3a2d9ac149662 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_73_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_73 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_73 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_73` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_73_en_5.1.4_3.4_1698223219896.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_73_en_5.1.4_3.4_1698223219896.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_73","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_73","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_73| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-73 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_74_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_74_en.md new file mode 100644 index 00000000000000..2d4bc553a6b360 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_74_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_74 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_74 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_74` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_74_en_5.1.4_3.4_1698223397781.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_74_en_5.1.4_3.4_1698223397781.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_74","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_74","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_74| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-74 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_75_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_75_en.md new file mode 100644 index 00000000000000..c6b7e2cf9c1edd --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_75_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_75 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_75 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_75` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_75_en_5.1.4_3.4_1698223965234.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_75_en_5.1.4_3.4_1698223965234.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_75","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_75","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_75| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-75 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_76_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_76_en.md new file mode 100644 index 00000000000000..0084c059fa22af --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_76_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_76 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_76 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_76` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_76_en_5.1.4_3.4_1698240706542.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_76_en_5.1.4_3.4_1698240706542.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_76","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_76","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_76| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-76 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_77_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_77_en.md new file mode 100644 index 00000000000000..24e5ce5121f174 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_77_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_77 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_77 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_77` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_77_en_5.1.4_3.4_1698241641782.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_77_en_5.1.4_3.4_1698241641782.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_77","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_77","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_77| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-77 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_78_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_78_en.md new file mode 100644 index 00000000000000..35654fca346898 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_78_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_78 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_78 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_78` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_78_en_5.1.4_3.4_1698254237854.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_78_en_5.1.4_3.4_1698254237854.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_78","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_78","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_78| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-78 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_79_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_79_en.md new file mode 100644 index 00000000000000..7bdab1fc191d1d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_79_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_79 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_79 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_79` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_79_en_5.1.4_3.4_1698253479821.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_79_en_5.1.4_3.4_1698253479821.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_79","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_79","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_79| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-79 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_7_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_7_en.md new file mode 100644 index 00000000000000..bbdf3063cbbc45 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_7_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_7 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_7 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_7` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_7_en_5.1.4_3.4_1698215109535.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_7_en_5.1.4_3.4_1698215109535.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_7","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_7","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_7| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-7 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_80_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_80_en.md new file mode 100644 index 00000000000000..b9a7a87df6b6f1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_80_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_80 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_80 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_80` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_80_en_5.1.4_3.4_1698255160718.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_80_en_5.1.4_3.4_1698255160718.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_80","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_80","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_80| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-80 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_81_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_81_en.md new file mode 100644 index 00000000000000..11f590ad3c0e39 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_81_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_81 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_81 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_81` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_81_en_5.1.4_3.4_1698242418276.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_81_en_5.1.4_3.4_1698242418276.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_81","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_81","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_81| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-81 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_82_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_82_en.md new file mode 100644 index 00000000000000..c90ed243a1122c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_82_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_82 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_82 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_82` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_82_en_5.1.4_3.4_1698245210556.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_82_en_5.1.4_3.4_1698245210556.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_82","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_82","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_82| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-82 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_83_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_83_en.md new file mode 100644 index 00000000000000..a2add8f63a0ebc --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_83_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_83 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_83 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_83` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_83_en_5.1.4_3.4_1698251953324.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_83_en_5.1.4_3.4_1698251953324.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_83","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_83","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_83| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-83 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_84_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_84_en.md new file mode 100644 index 00000000000000..ca21133556868d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_84_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_84 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_84 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_84` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_84_en_5.1.4_3.4_1698251201168.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_84_en_5.1.4_3.4_1698251201168.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_84","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_84","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_84| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-84 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_85_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_85_en.md new file mode 100644 index 00000000000000..281e6b0d2ecaaf --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_85_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_85 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_85 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_85` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_85_en_5.1.4_3.4_1698252780778.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_85_en_5.1.4_3.4_1698252780778.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_85","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_85","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_85| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-85 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_86_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_86_en.md new file mode 100644 index 00000000000000..3466fadb0f31c3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_86_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_86 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_86 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_86` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_86_en_5.1.4_3.4_1698248341656.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_86_en_5.1.4_3.4_1698248341656.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_86","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_86","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_86| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-86 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_87_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_87_en.md new file mode 100644 index 00000000000000..7a514aa240f585 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_87_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_87 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_87 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_87` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_87_en_5.1.4_3.4_1698247468504.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_87_en_5.1.4_3.4_1698247468504.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_87","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_87","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_87| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-87 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_88_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_88_en.md new file mode 100644 index 00000000000000..b3a64774ab8e19 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_88_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_88 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_88 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_88` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_88_en_5.1.4_3.4_1698246785005.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_88_en_5.1.4_3.4_1698246785005.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_88","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_88","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_88| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-88 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_89_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_89_en.md new file mode 100644 index 00000000000000..104864c31bf932 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_89_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_89 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_89 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_89` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_89_en_5.1.4_3.4_1698244522753.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_89_en_5.1.4_3.4_1698244522753.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_89","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_89","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_89| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-89 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_8_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_8_en.md new file mode 100644 index 00000000000000..381685395a6aa8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_8_en_5.1.4_3.4_1698215663747.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_8_en_5.1.4_3.4_1698215663747.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_91_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_91_en.md new file mode 100644 index 00000000000000..f9779e0c363f8b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_91_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_91 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_91 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_91` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_91_en_5.1.4_3.4_1698243759493.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_91_en_5.1.4_3.4_1698243759493.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_91","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_91","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_91| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-91 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_92_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_92_en.md new file mode 100644 index 00000000000000..90c44883d204e6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_92_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_92 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_92 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_92` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_92_en_5.1.4_3.4_1698249166450.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_92_en_5.1.4_3.4_1698249166450.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_92","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_92","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_92| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-92 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_93_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_93_en.md new file mode 100644 index 00000000000000..b0c97c30632cb7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_93_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_93 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_93 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_93` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_93_en_5.1.4_3.4_1698250033474.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_93_en_5.1.4_3.4_1698250033474.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_93","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_93","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_93| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-93 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_94_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_94_en.md new file mode 100644 index 00000000000000..8902eaac080cd7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_94_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_94 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_94 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_94` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_94_en_5.1.4_3.4_1698260494787.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_94_en_5.1.4_3.4_1698260494787.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_94","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_94","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_94| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-94 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_95_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_95_en.md new file mode 100644 index 00000000000000..5720bd611dd1bd --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_95_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_95 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_95 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_95` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_95_en_5.1.4_3.4_1698257018191.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_95_en_5.1.4_3.4_1698257018191.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_95","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_95","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_95| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-95 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_96_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_96_en.md new file mode 100644 index 00000000000000..cb12b9c5c8cfd3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_96_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_96 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_96 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_96` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_96_en_5.1.4_3.4_1698257719496.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_96_en_5.1.4_3.4_1698257719496.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_96","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_96","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_96| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-96 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_97_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_97_en.md new file mode 100644 index 00000000000000..1aff33221e951d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_97_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_97 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_97 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_97` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_97_en_5.1.4_3.4_1698259651200.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_97_en_5.1.4_3.4_1698259651200.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_97","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_97","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_97| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-97 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_98_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_98_en.md new file mode 100644 index 00000000000000..2093f7c7259197 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_98_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_98 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_98 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_98` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_98_en_5.1.4_3.4_1698258612165.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_98_en_5.1.4_3.4_1698258612165.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_98","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_98","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_98| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-98 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_99_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_99_en.md new file mode 100644 index 00000000000000..66d2d17970cf0d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_99_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_99 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_99 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_99` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_99_en_5.1.4_3.4_1698256093328.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_99_en_5.1.4_3.4_1698256093328.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_99","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_99","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_99| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-99 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_9_en.md b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_9_en.md new file mode 100644 index 00000000000000..f63cd5d3f30d5c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-goog_bert_ft_cola_9_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English goog_bert_ft_cola_9 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: goog_bert_ft_cola_9 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`goog_bert_ft_cola_9` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_9_en_5.1.4_3.4_1698215840044.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/goog_bert_ft_cola_9_en_5.1.4_3.4_1698215840044.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_9","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("goog_bert_ft_cola_9","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|goog_bert_ft_cola_9| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/goog_bert_ft_cola-9 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-hate_bert_model_en.md b/docs/_posts/ahmedlone127/2023-10-25-hate_bert_model_en.md new file mode 100644 index 00000000000000..c3ab9f0eed7034 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-hate_bert_model_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English hate_bert_model BertForSequenceClassification from warrior1127 +author: John Snow Labs +name: hate_bert_model +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hate_bert_model` is a English model originally trained by warrior1127. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hate_bert_model_en_5.1.4_3.4_1698197432839.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hate_bert_model_en_5.1.4_3.4_1698197432839.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("hate_bert_model","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("hate_bert_model","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hate_bert_model| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/warrior1127/hate_bert_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-hate_v1_final_bert_base_spanish_wwm_cased_en.md b/docs/_posts/ahmedlone127/2023-10-25-hate_v1_final_bert_base_spanish_wwm_cased_en.md new file mode 100644 index 00000000000000..ac81c1e69a8277 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-hate_v1_final_bert_base_spanish_wwm_cased_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English hate_v1_final_bert_base_spanish_wwm_cased BertForSequenceClassification from jorgeortizfuentes +author: John Snow Labs +name: hate_v1_final_bert_base_spanish_wwm_cased +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hate_v1_final_bert_base_spanish_wwm_cased` is a English model originally trained by jorgeortizfuentes. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hate_v1_final_bert_base_spanish_wwm_cased_en_5.1.4_3.4_1698209177130.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hate_v1_final_bert_base_spanish_wwm_cased_en_5.1.4_3.4_1698209177130.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("hate_v1_final_bert_base_spanish_wwm_cased","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("hate_v1_final_bert_base_spanish_wwm_cased","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hate_v1_final_bert_base_spanish_wwm_cased| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.7 MB| + +## References + +https://huggingface.co/jorgeortizfuentes/hate_v1_final-bert-base-spanish-wwm-cased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-hate_v2_final_tulio_chilean_spanish_bert_en.md b/docs/_posts/ahmedlone127/2023-10-25-hate_v2_final_tulio_chilean_spanish_bert_en.md new file mode 100644 index 00000000000000..1cad6d7881d809 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-hate_v2_final_tulio_chilean_spanish_bert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English hate_v2_final_tulio_chilean_spanish_bert BertForSequenceClassification from jorgeortizfuentes +author: John Snow Labs +name: hate_v2_final_tulio_chilean_spanish_bert +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hate_v2_final_tulio_chilean_spanish_bert` is a English model originally trained by jorgeortizfuentes. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hate_v2_final_tulio_chilean_spanish_bert_en_5.1.4_3.4_1698209578952.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hate_v2_final_tulio_chilean_spanish_bert_en_5.1.4_3.4_1698209578952.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("hate_v2_final_tulio_chilean_spanish_bert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("hate_v2_final_tulio_chilean_spanish_bert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hate_v2_final_tulio_chilean_spanish_bert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.5 MB| + +## References + +https://huggingface.co/jorgeortizfuentes/hate_v2_final-tulio-chilean-spanish-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-hatebert_ishate_29k_en.md b/docs/_posts/ahmedlone127/2023-10-25-hatebert_ishate_29k_en.md new file mode 100644 index 00000000000000..fe9fb6d3cf007e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-hatebert_ishate_29k_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English hatebert_ishate_29k BertForSequenceClassification from bitsanlp +author: John Snow Labs +name: hatebert_ishate_29k +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hatebert_ishate_29k` is a English model originally trained by bitsanlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hatebert_ishate_29k_en_5.1.4_3.4_1698205841546.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hatebert_ishate_29k_en_5.1.4_3.4_1698205841546.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("hatebert_ishate_29k","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("hatebert_ishate_29k","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hatebert_ishate_29k| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|408.3 MB| + +## References + +https://huggingface.co/bitsanlp/hatebert-ishate-29k \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-hindi_const21_hibert_final_en.md b/docs/_posts/ahmedlone127/2023-10-25-hindi_const21_hibert_final_en.md new file mode 100644 index 00000000000000..67a0c24f3195c4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-hindi_const21_hibert_final_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English hindi_const21_hibert_final BertForSequenceClassification from Maha +author: John Snow Labs +name: hindi_const21_hibert_final +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`hindi_const21_hibert_final` is a English model originally trained by Maha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/hindi_const21_hibert_final_en_5.1.4_3.4_1698224332652.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/hindi_const21_hibert_final_en_5.1.4_3.4_1698224332652.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("hindi_const21_hibert_final","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("hindi_const21_hibert_final","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|hindi_const21_hibert_final| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|611.4 MB| + +## References + +https://huggingface.co/Maha/hi-const21-hibert_final \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-human_needs_bert_2_en.md b/docs/_posts/ahmedlone127/2023-10-25-human_needs_bert_2_en.md new file mode 100644 index 00000000000000..fe12b91726415c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-human_needs_bert_2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English human_needs_bert_2 BertForSequenceClassification from zzhifz +author: John Snow Labs +name: human_needs_bert_2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`human_needs_bert_2` is a English model originally trained by zzhifz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/human_needs_bert_2_en_5.1.4_3.4_1698198722764.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/human_needs_bert_2_en_5.1.4_3.4_1698198722764.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("human_needs_bert_2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("human_needs_bert_2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|human_needs_bert_2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|410.0 MB| + +## References + +https://huggingface.co/zzhifz/human-needs-bert-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-human_needs_bert_en.md b/docs/_posts/ahmedlone127/2023-10-25-human_needs_bert_en.md new file mode 100644 index 00000000000000..eb326e33fcc16a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-human_needs_bert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English human_needs_bert BertForSequenceClassification from zzhifz +author: John Snow Labs +name: human_needs_bert +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`human_needs_bert` is a English model originally trained by zzhifz. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/human_needs_bert_en_5.1.4_3.4_1698196941016.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/human_needs_bert_en_5.1.4_3.4_1698196941016.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("human_needs_bert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("human_needs_bert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|human_needs_bert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/zzhifz/human-needs-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-imdb_bert_base_uncased_kyle1668_en.md b/docs/_posts/ahmedlone127/2023-10-25-imdb_bert_base_uncased_kyle1668_en.md new file mode 100644 index 00000000000000..6d891cd33a40bd --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-imdb_bert_base_uncased_kyle1668_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English imdb_bert_base_uncased_kyle1668 BertForSequenceClassification from Kyle1668 +author: John Snow Labs +name: imdb_bert_base_uncased_kyle1668 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`imdb_bert_base_uncased_kyle1668` is a English model originally trained by Kyle1668. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/imdb_bert_base_uncased_kyle1668_en_5.1.4_3.4_1698246411737.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/imdb_bert_base_uncased_kyle1668_en_5.1.4_3.4_1698246411737.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("imdb_bert_base_uncased_kyle1668","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("imdb_bert_base_uncased_kyle1668","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|imdb_bert_base_uncased_kyle1668| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Kyle1668/imdb-bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-incivility_v1_final_tulio_chilean_spanish_bert_en.md b/docs/_posts/ahmedlone127/2023-10-25-incivility_v1_final_tulio_chilean_spanish_bert_en.md new file mode 100644 index 00000000000000..975b056ce8c817 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-incivility_v1_final_tulio_chilean_spanish_bert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English incivility_v1_final_tulio_chilean_spanish_bert BertForSequenceClassification from jorgeortizfuentes +author: John Snow Labs +name: incivility_v1_final_tulio_chilean_spanish_bert +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`incivility_v1_final_tulio_chilean_spanish_bert` is a English model originally trained by jorgeortizfuentes. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/incivility_v1_final_tulio_chilean_spanish_bert_en_5.1.4_3.4_1698209376203.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/incivility_v1_final_tulio_chilean_spanish_bert_en_5.1.4_3.4_1698209376203.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("incivility_v1_final_tulio_chilean_spanish_bert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("incivility_v1_final_tulio_chilean_spanish_bert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|incivility_v1_final_tulio_chilean_spanish_bert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.5 MB| + +## References + +https://huggingface.co/jorgeortizfuentes/incivility_v1_final-tulio-chilean-spanish-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-incivility_v2_final_tulio_chilean_spanish_bert_en.md b/docs/_posts/ahmedlone127/2023-10-25-incivility_v2_final_tulio_chilean_spanish_bert_en.md new file mode 100644 index 00000000000000..b2d9d776af8270 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-incivility_v2_final_tulio_chilean_spanish_bert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English incivility_v2_final_tulio_chilean_spanish_bert BertForSequenceClassification from jorgeortizfuentes +author: John Snow Labs +name: incivility_v2_final_tulio_chilean_spanish_bert +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`incivility_v2_final_tulio_chilean_spanish_bert` is a English model originally trained by jorgeortizfuentes. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/incivility_v2_final_tulio_chilean_spanish_bert_en_5.1.4_3.4_1698209746645.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/incivility_v2_final_tulio_chilean_spanish_bert_en_5.1.4_3.4_1698209746645.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("incivility_v2_final_tulio_chilean_spanish_bert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("incivility_v2_final_tulio_chilean_spanish_bert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|incivility_v2_final_tulio_chilean_spanish_bert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.5 MB| + +## References + +https://huggingface.co/jorgeortizfuentes/incivility_v2_final-tulio-chilean-spanish-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-indobertnews_en.md b/docs/_posts/ahmedlone127/2023-10-25-indobertnews_en.md new file mode 100644 index 00000000000000..fa30240738f2e3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-indobertnews_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English indobertnews BertForSequenceClassification from mrizalf7 +author: John Snow Labs +name: indobertnews +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indobertnews` is a English model originally trained by mrizalf7. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indobertnews_en_5.1.4_3.4_1698206635949.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indobertnews_en_5.1.4_3.4_1698206635949.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("indobertnews","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("indobertnews","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indobertnews| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.0 MB| + +## References + +https://huggingface.co/mrizalf7/IndobertNews \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-indobertnewstest_dimassamid_en.md b/docs/_posts/ahmedlone127/2023-10-25-indobertnewstest_dimassamid_en.md new file mode 100644 index 00000000000000..aab39d55afa3a8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-indobertnewstest_dimassamid_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English indobertnewstest_dimassamid BertForSequenceClassification from dimassamid +author: John Snow Labs +name: indobertnewstest_dimassamid +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indobertnewstest_dimassamid` is a English model originally trained by dimassamid. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indobertnewstest_dimassamid_en_5.1.4_3.4_1698211212020.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indobertnewstest_dimassamid_en_5.1.4_3.4_1698211212020.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("indobertnewstest_dimassamid","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("indobertnewstest_dimassamid","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indobertnewstest_dimassamid| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.0 MB| + +## References + +https://huggingface.co/dimassamid/IndobertNewsTest \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-indobertnewstest_rizalmilyardi_en.md b/docs/_posts/ahmedlone127/2023-10-25-indobertnewstest_rizalmilyardi_en.md new file mode 100644 index 00000000000000..461c447d6d40dc --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-indobertnewstest_rizalmilyardi_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English indobertnewstest_rizalmilyardi BertForSequenceClassification from rizalmilyardi +author: John Snow Labs +name: indobertnewstest_rizalmilyardi +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indobertnewstest_rizalmilyardi` is a English model originally trained by rizalmilyardi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indobertnewstest_rizalmilyardi_en_5.1.4_3.4_1698211956208.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indobertnewstest_rizalmilyardi_en_5.1.4_3.4_1698211956208.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("indobertnewstest_rizalmilyardi","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("indobertnewstest_rizalmilyardi","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indobertnewstest_rizalmilyardi| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.0 MB| + +## References + +https://huggingface.co/rizalmilyardi/IndobertNewsTest \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-indoberttypenews_en.md b/docs/_posts/ahmedlone127/2023-10-25-indoberttypenews_en.md new file mode 100644 index 00000000000000..9afca701315a0f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-indoberttypenews_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English indoberttypenews BertForSequenceClassification from rizalmilyardi +author: John Snow Labs +name: indoberttypenews +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`indoberttypenews` is a English model originally trained by rizalmilyardi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/indoberttypenews_en_5.1.4_3.4_1698210826631.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/indoberttypenews_en_5.1.4_3.4_1698210826631.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("indoberttypenews","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("indoberttypenews","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|indoberttypenews| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|413.9 MB| + +## References + +https://huggingface.co/rizalmilyardi/IndobertTypeNews \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-kcbert_en.md b/docs/_posts/ahmedlone127/2023-10-25-kcbert_en.md new file mode 100644 index 00000000000000..11f1e0535b5962 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-kcbert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English kcbert BertForSequenceClassification from jiiyy +author: John Snow Labs +name: kcbert +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kcbert` is a English model originally trained by jiiyy. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kcbert_en_5.1.4_3.4_1698257627926.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kcbert_en_5.1.4_3.4_1698257627926.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("kcbert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("kcbert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kcbert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|408.4 MB| + +## References + +https://huggingface.co/jiiyy/kcbert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-klue_bert_base_re_ainize_en.md b/docs/_posts/ahmedlone127/2023-10-25-klue_bert_base_re_ainize_en.md new file mode 100644 index 00000000000000..cab0aa0a501d53 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-klue_bert_base_re_ainize_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English klue_bert_base_re_ainize BertForSequenceClassification from ainize +author: John Snow Labs +name: klue_bert_base_re_ainize +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`klue_bert_base_re_ainize` is a English model originally trained by ainize. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/klue_bert_base_re_ainize_en_5.1.4_3.4_1698276026066.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/klue_bert_base_re_ainize_en_5.1.4_3.4_1698276026066.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("klue_bert_base_re_ainize","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("klue_bert_base_re_ainize","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|klue_bert_base_re_ainize| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.7 MB| + +## References + +https://huggingface.co/ainize/klue-bert-base-re \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-klue_bert_finetuned_nsmc_en.md b/docs/_posts/ahmedlone127/2023-10-25-klue_bert_finetuned_nsmc_en.md new file mode 100644 index 00000000000000..b6f9ca30d96d25 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-klue_bert_finetuned_nsmc_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English klue_bert_finetuned_nsmc BertForSequenceClassification from PlayDev +author: John Snow Labs +name: klue_bert_finetuned_nsmc +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`klue_bert_finetuned_nsmc` is a English model originally trained by PlayDev. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/klue_bert_finetuned_nsmc_en_5.1.4_3.4_1698193370011.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/klue_bert_finetuned_nsmc_en_5.1.4_3.4_1698193370011.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("klue_bert_finetuned_nsmc","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("klue_bert_finetuned_nsmc","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|klue_bert_finetuned_nsmc| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.6 MB| + +## References + +https://huggingface.co/PlayDev/klue-bert-finetuned-nsmc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-knots_protbertbfd_alphafold_evaklimentova_en.md b/docs/_posts/ahmedlone127/2023-10-25-knots_protbertbfd_alphafold_evaklimentova_en.md new file mode 100644 index 00000000000000..0ea896d4c92b78 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-knots_protbertbfd_alphafold_evaklimentova_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English knots_protbertbfd_alphafold_evaklimentova BertForSequenceClassification from EvaKlimentova +author: John Snow Labs +name: knots_protbertbfd_alphafold_evaklimentova +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`knots_protbertbfd_alphafold_evaklimentova` is a English model originally trained by EvaKlimentova. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/knots_protbertbfd_alphafold_evaklimentova_en_5.1.4_3.4_1698198794585.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/knots_protbertbfd_alphafold_evaklimentova_en_5.1.4_3.4_1698198794585.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("knots_protbertbfd_alphafold_evaklimentova","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("knots_protbertbfd_alphafold_evaklimentova","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|knots_protbertbfd_alphafold_evaklimentova| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/EvaKlimentova/knots_protbertBFD_alphafold \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-knots_protbertbfd_alphafold_roa7n_en.md b/docs/_posts/ahmedlone127/2023-10-25-knots_protbertbfd_alphafold_roa7n_en.md new file mode 100644 index 00000000000000..82df3a47e922dd --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-knots_protbertbfd_alphafold_roa7n_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English knots_protbertbfd_alphafold_roa7n BertForSequenceClassification from roa7n +author: John Snow Labs +name: knots_protbertbfd_alphafold_roa7n +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`knots_protbertbfd_alphafold_roa7n` is a English model originally trained by roa7n. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/knots_protbertbfd_alphafold_roa7n_en_5.1.4_3.4_1698216194692.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/knots_protbertbfd_alphafold_roa7n_en_5.1.4_3.4_1698216194692.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("knots_protbertbfd_alphafold_roa7n","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("knots_protbertbfd_alphafold_roa7n","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|knots_protbertbfd_alphafold_roa7n| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/roa7n/knots_protbertBFD_alphafold \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-kobert_esg_en.md b/docs/_posts/ahmedlone127/2023-10-25-kobert_esg_en.md new file mode 100644 index 00000000000000..e423578bfcea39 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-kobert_esg_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English kobert_esg BertForSequenceClassification from keonju +author: John Snow Labs +name: kobert_esg +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kobert_esg` is a English model originally trained by keonju. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kobert_esg_en_5.1.4_3.4_1698213440220.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kobert_esg_en_5.1.4_3.4_1698213440220.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("kobert_esg","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("kobert_esg","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kobert_esg| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|345.1 MB| + +## References + +https://huggingface.co/keonju/kobert_ESG \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-kobert_senti_en.md b/docs/_posts/ahmedlone127/2023-10-25-kobert_senti_en.md new file mode 100644 index 00000000000000..cb16e37e9d3873 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-kobert_senti_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English kobert_senti BertForSequenceClassification from keonju +author: John Snow Labs +name: kobert_senti +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kobert_senti` is a English model originally trained by keonju. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kobert_senti_en_5.1.4_3.4_1698206798000.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kobert_senti_en_5.1.4_3.4_1698206798000.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("kobert_senti","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("kobert_senti","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kobert_senti| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|345.1 MB| + +## References + +https://huggingface.co/keonju/kobert_senti \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-legal_bert_based_uncase_en.md b/docs/_posts/ahmedlone127/2023-10-25-legal_bert_based_uncase_en.md new file mode 100644 index 00000000000000..f1abf912760c7c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-legal_bert_based_uncase_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English legal_bert_based_uncase BertForSequenceClassification from amanbawa96 +author: John Snow Labs +name: legal_bert_based_uncase +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_bert_based_uncase` is a English model originally trained by amanbawa96. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_bert_based_uncase_en_5.1.4_3.4_1698264650160.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_bert_based_uncase_en_5.1.4_3.4_1698264650160.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("legal_bert_based_uncase","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("legal_bert_based_uncase","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|legal_bert_based_uncase| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.6 MB| + +## References + +https://huggingface.co/amanbawa96/legal-bert-based-uncase \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-legal_bert_tpb_clause_class_en.md b/docs/_posts/ahmedlone127/2023-10-25-legal_bert_tpb_clause_class_en.md new file mode 100644 index 00000000000000..db9dffa14be5d4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-legal_bert_tpb_clause_class_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English legal_bert_tpb_clause_class BertForSequenceClassification from frankkuete +author: John Snow Labs +name: legal_bert_tpb_clause_class +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`legal_bert_tpb_clause_class` is a English model originally trained by frankkuete. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/legal_bert_tpb_clause_class_en_5.1.4_3.4_1698237815681.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/legal_bert_tpb_clause_class_en_5.1.4_3.4_1698237815681.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("legal_bert_tpb_clause_class","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("legal_bert_tpb_clause_class","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|legal_bert_tpb_clause_class| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/frankkuete/legal-bert-tpb-clause-class \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-macedonian_bert_sentiment_classification_4labels_en.md b/docs/_posts/ahmedlone127/2023-10-25-macedonian_bert_sentiment_classification_4labels_en.md new file mode 100644 index 00000000000000..a38f01f4e8cf73 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-macedonian_bert_sentiment_classification_4labels_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English macedonian_bert_sentiment_classification_4labels BertForSequenceClassification from mk9165 +author: John Snow Labs +name: macedonian_bert_sentiment_classification_4labels +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`macedonian_bert_sentiment_classification_4labels` is a English model originally trained by mk9165. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/macedonian_bert_sentiment_classification_4labels_en_5.1.4_3.4_1698208948044.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/macedonian_bert_sentiment_classification_4labels_en_5.1.4_3.4_1698208948044.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("macedonian_bert_sentiment_classification_4labels","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("macedonian_bert_sentiment_classification_4labels","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|macedonian_bert_sentiment_classification_4labels| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|443.4 MB| + +## References + +https://huggingface.co/mk9165/mk-bert-sentiment-classification-4labels \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-macedonian_bert_sentiment_classification_en.md b/docs/_posts/ahmedlone127/2023-10-25-macedonian_bert_sentiment_classification_en.md new file mode 100644 index 00000000000000..4b0cd2b74e8ef4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-macedonian_bert_sentiment_classification_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English macedonian_bert_sentiment_classification BertForSequenceClassification from mk9165 +author: John Snow Labs +name: macedonian_bert_sentiment_classification +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`macedonian_bert_sentiment_classification` is a English model originally trained by mk9165. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/macedonian_bert_sentiment_classification_en_5.1.4_3.4_1698196985187.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/macedonian_bert_sentiment_classification_en_5.1.4_3.4_1698196985187.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("macedonian_bert_sentiment_classification","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("macedonian_bert_sentiment_classification","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|macedonian_bert_sentiment_classification| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|443.4 MB| + +## References + +https://huggingface.co/mk9165/mk-bert-sentiment-classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-mascorpus_bert_classifier_en.md b/docs/_posts/ahmedlone127/2023-10-25-mascorpus_bert_classifier_en.md new file mode 100644 index 00000000000000..9279c06b51faff --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-mascorpus_bert_classifier_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English mascorpus_bert_classifier BertForSequenceClassification from fce-m72109 +author: John Snow Labs +name: mascorpus_bert_classifier +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mascorpus_bert_classifier` is a English model originally trained by fce-m72109. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mascorpus_bert_classifier_en_5.1.4_3.4_1698271464648.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mascorpus_bert_classifier_en_5.1.4_3.4_1698271464648.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("mascorpus_bert_classifier","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mascorpus_bert_classifier","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mascorpus_bert_classifier| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.9 MB| + +## References + +https://huggingface.co/fce-m72109/mascorpus-bert-classifier \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-mbert_base_cased_finetuned_bengali_fakenews_en.md b/docs/_posts/ahmedlone127/2023-10-25-mbert_base_cased_finetuned_bengali_fakenews_en.md new file mode 100644 index 00000000000000..0ad242d94b15b8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-mbert_base_cased_finetuned_bengali_fakenews_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English mbert_base_cased_finetuned_bengali_fakenews BertForSequenceClassification from DeadBeast +author: John Snow Labs +name: mbert_base_cased_finetuned_bengali_fakenews +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mbert_base_cased_finetuned_bengali_fakenews` is a English model originally trained by DeadBeast. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mbert_base_cased_finetuned_bengali_fakenews_en_5.1.4_3.4_1698193902726.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mbert_base_cased_finetuned_bengali_fakenews_en_5.1.4_3.4_1698193902726.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("mbert_base_cased_finetuned_bengali_fakenews","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mbert_base_cased_finetuned_bengali_fakenews","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mbert_base_cased_finetuned_bengali_fakenews| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|667.3 MB| + +## References + +https://huggingface.co/DeadBeast/mbert-base-cased-finetuned-bengali-fakenews \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1_zh.md b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1_zh.md new file mode 100644 index 00000000000000..0d29001ba17803 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1_zh.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Chinese mengzi_bert_base_fin_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: mengzi_bert_base_fin_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1 +date: 2023-10-25 +tags: [bert, zh, open_source, sequence_classification, onnx] +task: Text Classification +language: zh +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mengzi_bert_base_fin_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1` is a Chinese model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1_zh_5.1.4_3.4_1698213915520.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1_zh_5.1.4_3.4_1698213915520.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1","zh")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1","zh") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mengzi_bert_base_fin_finetuning_wallstreetcn_morning_news_market_overview_open_000001sh_v1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|zh| +|Size:|383.1 MB| + +## References + +https://huggingface.co/hw2942/mengzi-bert-base-fin-finetuning-wallstreetcn-morning-news-market-overview-open-000001SH-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_ssec_en.md b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_ssec_en.md new file mode 100644 index 00000000000000..9ad40abc891aba --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_ssec_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English mengzi_bert_base_fin_ssec BertForSequenceClassification from hw2942 +author: John Snow Labs +name: mengzi_bert_base_fin_ssec +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mengzi_bert_base_fin_ssec` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_ssec_en_5.1.4_3.4_1698222925679.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_ssec_en_5.1.4_3.4_1698222925679.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_ssec","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_ssec","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mengzi_bert_base_fin_ssec| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.1 MB| + +## References + +https://huggingface.co/hw2942/mengzi-bert-base-fin-SSEC \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_f1_v1_en.md b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_f1_v1_en.md new file mode 100644 index 00000000000000..7609c326cdf263 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_f1_v1_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_f1_v1 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_f1_v1 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_f1_v1` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_f1_v1_en_5.1.4_3.4_1698219379071.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_f1_v1_en_5.1.4_3.4_1698219379071.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_f1_v1","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_f1_v1","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_f1_v1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.1 MB| + +## References + +https://huggingface.co/hw2942/mengzi-bert-base-fin-wallstreetcn-morning-news-market-overview-open-SSEC-f1-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_f1_v22_en.md b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_f1_v22_en.md new file mode 100644 index 00000000000000..3cff0c16472972 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_f1_v22_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_f1_v22 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_f1_v22 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_f1_v22` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_f1_v22_en_5.1.4_3.4_1698223114906.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_f1_v22_en_5.1.4_3.4_1698223114906.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_f1_v22","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_f1_v22","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_f1_v22| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.1 MB| + +## References + +https://huggingface.co/hw2942/mengzi-bert-base-fin-wallstreetcn-morning-news-market-overview-open-SSEC-f1-v22 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_v2_en.md b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_v2_en.md new file mode 100644 index 00000000000000..db46416dce0017 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_v2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_v2 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_v2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_v2` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_v2_en_5.1.4_3.4_1698220731080.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_v2_en_5.1.4_3.4_1698220731080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_v2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_v2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_open_ssec_v2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.1 MB| + +## References + +https://huggingface.co/hw2942/mengzi-bert-base-fin-wallstreetcn-morning-news-market-overview-open-SSEC-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_10_en.md b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_10_en.md new file mode 100644 index 00000000000000..690f7962a21139 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_10_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_10 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_10 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_10` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_10_en_5.1.4_3.4_1698276807226.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_10_en_5.1.4_3.4_1698276807226.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_10","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_10","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_10| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.1 MB| + +## References + +https://huggingface.co/hw2942/mengzi-bert-base-fin-wallstreetcn-morning-news-market-overview-SSEC-10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_1_en.md b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_1_en.md new file mode 100644 index 00000000000000..449cf891785747 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_1_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_1 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_1 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_1` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_1_en_5.1.4_3.4_1698269142584.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_1_en_5.1.4_3.4_1698269142584.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_1","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_1","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.1 MB| + +## References + +https://huggingface.co/hw2942/mengzi-bert-base-fin-wallstreetcn-morning-news-market-overview-SSEC-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_2_en.md b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_2_en.md new file mode 100644 index 00000000000000..9898e35ba3109a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_2 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_2` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_2_en_5.1.4_3.4_1698270054619.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_2_en_5.1.4_3.4_1698270054619.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.1 MB| + +## References + +https://huggingface.co/hw2942/mengzi-bert-base-fin-wallstreetcn-morning-news-market-overview-SSEC-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_3_en.md b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_3_en.md new file mode 100644 index 00000000000000..6e8a3de4513985 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_3_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_3 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_3 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_3` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_3_en_5.1.4_3.4_1698270778170.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_3_en_5.1.4_3.4_1698270778170.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_3","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_3","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_3| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.1 MB| + +## References + +https://huggingface.co/hw2942/mengzi-bert-base-fin-wallstreetcn-morning-news-market-overview-SSEC-3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_4_en.md b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_4_en.md new file mode 100644 index 00000000000000..1a1992e3cd3e7a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_4_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_4 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_4 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_4` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_4_en_5.1.4_3.4_1698271547606.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_4_en_5.1.4_3.4_1698271547606.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_4","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_4","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_4| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.1 MB| + +## References + +https://huggingface.co/hw2942/mengzi-bert-base-fin-wallstreetcn-morning-news-market-overview-SSEC-4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_5_en.md b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_5_en.md new file mode 100644 index 00000000000000..cc2d1a49acd000 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_5_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_5 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_5 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_5` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_5_en_5.1.4_3.4_1698272598012.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_5_en_5.1.4_3.4_1698272598012.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_5","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_5","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_5| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.1 MB| + +## References + +https://huggingface.co/hw2942/mengzi-bert-base-fin-wallstreetcn-morning-news-market-overview-SSEC-5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_6_en.md b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_6_en.md new file mode 100644 index 00000000000000..9879b1bf039ef9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_6_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_6 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_6 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_6` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_6_en_5.1.4_3.4_1698273428030.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_6_en_5.1.4_3.4_1698273428030.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_6","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_6","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_6| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.1 MB| + +## References + +https://huggingface.co/hw2942/mengzi-bert-base-fin-wallstreetcn-morning-news-market-overview-SSEC-6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_7_en.md b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_7_en.md new file mode 100644 index 00000000000000..fbee242a58efe4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_7_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_7 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_7 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_7` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_7_en_5.1.4_3.4_1698274391531.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_7_en_5.1.4_3.4_1698274391531.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_7","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_7","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_7| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.1 MB| + +## References + +https://huggingface.co/hw2942/mengzi-bert-base-fin-wallstreetcn-morning-news-market-overview-SSEC-7 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_8_en.md b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_8_en.md new file mode 100644 index 00000000000000..c558821e6f6065 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_8 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_8` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_8_en_5.1.4_3.4_1698274939326.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_8_en_5.1.4_3.4_1698274939326.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.1 MB| + +## References + +https://huggingface.co/hw2942/mengzi-bert-base-fin-wallstreetcn-morning-news-market-overview-SSEC-8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_9_en.md b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_9_en.md new file mode 100644 index 00000000000000..12437995f69126 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_9_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_9 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_9 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_9` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_9_en_5.1.4_3.4_1698275862469.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_9_en_5.1.4_3.4_1698275862469.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_9","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_9","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_9| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.1 MB| + +## References + +https://huggingface.co/hw2942/mengzi-bert-base-fin-wallstreetcn-morning-news-market-overview-SSEC-9 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-mental_bert_base_uncased_finetuned_0505_en.md b/docs/_posts/ahmedlone127/2023-10-25-mental_bert_base_uncased_finetuned_0505_en.md new file mode 100644 index 00000000000000..3a97ef7a3f405a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-mental_bert_base_uncased_finetuned_0505_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English mental_bert_base_uncased_finetuned_0505 BertForSequenceClassification from YeRyeongLee +author: John Snow Labs +name: mental_bert_base_uncased_finetuned_0505 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mental_bert_base_uncased_finetuned_0505` is a English model originally trained by YeRyeongLee. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mental_bert_base_uncased_finetuned_0505_en_5.1.4_3.4_1698201411316.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mental_bert_base_uncased_finetuned_0505_en_5.1.4_3.4_1698201411316.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("mental_bert_base_uncased_finetuned_0505","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mental_bert_base_uncased_finetuned_0505","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mental_bert_base_uncased_finetuned_0505| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|408.8 MB| + +## References + +https://huggingface.co/YeRyeongLee/mental-bert-base-uncased-finetuned-0505 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-mini_bert_distilled_en.md b/docs/_posts/ahmedlone127/2023-10-25-mini_bert_distilled_en.md new file mode 100644 index 00000000000000..19b3cb261a694c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-mini_bert_distilled_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English mini_bert_distilled BertForSequenceClassification from moshew +author: John Snow Labs +name: mini_bert_distilled +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mini_bert_distilled` is a English model originally trained by moshew. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mini_bert_distilled_en_5.1.4_3.4_1698240255617.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mini_bert_distilled_en_5.1.4_3.4_1698240255617.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("mini_bert_distilled","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mini_bert_distilled","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mini_bert_distilled| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|42.2 MB| + +## References + +https://huggingface.co/moshew/Mini-bert-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-ml_ns_bert_base_uncased_en.md b/docs/_posts/ahmedlone127/2023-10-25-ml_ns_bert_base_uncased_en.md new file mode 100644 index 00000000000000..2d5811fc5ce2ca --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-ml_ns_bert_base_uncased_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English ml_ns_bert_base_uncased BertForSequenceClassification from sara-nabhani +author: John Snow Labs +name: ml_ns_bert_base_uncased +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ml_ns_bert_base_uncased` is a English model originally trained by sara-nabhani. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ml_ns_bert_base_uncased_en_5.1.4_3.4_1698194262921.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ml_ns_bert_base_uncased_en_5.1.4_3.4_1698194262921.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("ml_ns_bert_base_uncased","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("ml_ns_bert_base_uncased","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ml_ns_bert_base_uncased| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/sara-nabhani/ML-ns-bert-base-uncased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-ml_ns_finbert_en.md b/docs/_posts/ahmedlone127/2023-10-25-ml_ns_finbert_en.md new file mode 100644 index 00000000000000..781fa13d4c9cf0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-ml_ns_finbert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English ml_ns_finbert BertForSequenceClassification from sara-nabhani +author: John Snow Labs +name: ml_ns_finbert +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ml_ns_finbert` is a English model originally trained by sara-nabhani. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ml_ns_finbert_en_5.1.4_3.4_1698194077828.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ml_ns_finbert_en_5.1.4_3.4_1698194077828.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("ml_ns_finbert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("ml_ns_finbert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ml_ns_finbert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/sara-nabhani/ML-ns-finbert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-model3_marabertv2_t1_en.md b/docs/_posts/ahmedlone127/2023-10-25-model3_marabertv2_t1_en.md new file mode 100644 index 00000000000000..3cb7150d933069 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-model3_marabertv2_t1_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English model3_marabertv2_t1 BertForSequenceClassification from Somah +author: John Snow Labs +name: model3_marabertv2_t1 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model3_marabertv2_t1` is a English model originally trained by Somah. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model3_marabertv2_t1_en_5.1.4_3.4_1698268582056.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model3_marabertv2_t1_en_5.1.4_3.4_1698268582056.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("model3_marabertv2_t1","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("model3_marabertv2_t1","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model3_marabertv2_t1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|608.8 MB| + +## References + +https://huggingface.co/Somah/Model3_Marabertv2_T1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-mpe_bert_l_en.md b/docs/_posts/ahmedlone127/2023-10-25-mpe_bert_l_en.md new file mode 100644 index 00000000000000..a6a6d101b119d9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-mpe_bert_l_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English mpe_bert_l BertForSequenceClassification from veronica320 +author: John Snow Labs +name: mpe_bert_l +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mpe_bert_l` is a English model originally trained by veronica320. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mpe_bert_l_en_5.1.4_3.4_1698198372650.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mpe_bert_l_en_5.1.4_3.4_1698198372650.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("mpe_bert_l","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mpe_bert_l","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mpe_bert_l| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/veronica320/MPE_bert-l \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-multicite_multilabel_scibert_en.md b/docs/_posts/ahmedlone127/2023-10-25-multicite_multilabel_scibert_en.md new file mode 100644 index 00000000000000..6cd937cb2f1156 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-multicite_multilabel_scibert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English multicite_multilabel_scibert BertForSequenceClassification from allenai +author: John Snow Labs +name: multicite_multilabel_scibert +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multicite_multilabel_scibert` is a English model originally trained by allenai. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multicite_multilabel_scibert_en_5.1.4_3.4_1698202659603.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multicite_multilabel_scibert_en_5.1.4_3.4_1698202659603.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("multicite_multilabel_scibert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("multicite_multilabel_scibert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multicite_multilabel_scibert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|412.1 MB| + +## References + +https://huggingface.co/allenai/multicite-multilabel-scibert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-multilabel_earthquake_tweet_intent_bert_base_turkish_cased_tr.md b/docs/_posts/ahmedlone127/2023-10-25-multilabel_earthquake_tweet_intent_bert_base_turkish_cased_tr.md new file mode 100644 index 00000000000000..17056f5ecf68b4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-multilabel_earthquake_tweet_intent_bert_base_turkish_cased_tr.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Turkish multilabel_earthquake_tweet_intent_bert_base_turkish_cased BertForSequenceClassification from deprem-ml +author: John Snow Labs +name: multilabel_earthquake_tweet_intent_bert_base_turkish_cased +date: 2023-10-25 +tags: [bert, tr, open_source, sequence_classification, onnx] +task: Text Classification +language: tr +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`multilabel_earthquake_tweet_intent_bert_base_turkish_cased` is a Turkish model originally trained by deprem-ml. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/multilabel_earthquake_tweet_intent_bert_base_turkish_cased_tr_5.1.4_3.4_1698200263892.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/multilabel_earthquake_tweet_intent_bert_base_turkish_cased_tr_5.1.4_3.4_1698200263892.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("multilabel_earthquake_tweet_intent_bert_base_turkish_cased","tr")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("multilabel_earthquake_tweet_intent_bert_base_turkish_cased","tr") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|multilabel_earthquake_tweet_intent_bert_base_turkish_cased| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|tr| +|Size:|414.5 MB| + +## References + +https://huggingface.co/deprem-ml/multilabel_earthquake_tweet_intent_bert_base_turkish_cased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_12_en.md b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_12_en.md new file mode 100644 index 00000000000000..7e28c81857130f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_12_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English norbert2_sentiment_norec_12 BertForSequenceClassification from NTCAL +author: John Snow Labs +name: norbert2_sentiment_norec_12 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norbert2_sentiment_norec_12` is a English model originally trained by NTCAL. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_12_en_5.1.4_3.4_1698267978688.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_12_en_5.1.4_3.4_1698267978688.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec_12","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec_12","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norbert2_sentiment_norec_12| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/NTCAL/norbert2_sentiment_norec_12 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_13_en.md b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_13_en.md new file mode 100644 index 00000000000000..396647481e0cdd --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_13_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English norbert2_sentiment_norec_13 BertForSequenceClassification from NTCAL +author: John Snow Labs +name: norbert2_sentiment_norec_13 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norbert2_sentiment_norec_13` is a English model originally trained by NTCAL. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_13_en_5.1.4_3.4_1698271367051.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_13_en_5.1.4_3.4_1698271367051.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec_13","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec_13","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norbert2_sentiment_norec_13| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/NTCAL/norbert2_sentiment_norec_13 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_14_en.md b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_14_en.md new file mode 100644 index 00000000000000..99a892aa2819c5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_14_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English norbert2_sentiment_norec_14 BertForSequenceClassification from NTCAL +author: John Snow Labs +name: norbert2_sentiment_norec_14 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norbert2_sentiment_norec_14` is a English model originally trained by NTCAL. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_14_en_5.1.4_3.4_1698273021725.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_14_en_5.1.4_3.4_1698273021725.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec_14","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec_14","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norbert2_sentiment_norec_14| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/NTCAL/norbert2_sentiment_norec_14 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_16_en.md b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_16_en.md new file mode 100644 index 00000000000000..6b9f4b229200e7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_16_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English norbert2_sentiment_norec_16 BertForSequenceClassification from NTCAL +author: John Snow Labs +name: norbert2_sentiment_norec_16 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norbert2_sentiment_norec_16` is a English model originally trained by NTCAL. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_16_en_5.1.4_3.4_1698274392887.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_16_en_5.1.4_3.4_1698274392887.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec_16","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec_16","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norbert2_sentiment_norec_16| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/NTCAL/norbert2_sentiment_norec_16 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_2_en.md b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_2_en.md new file mode 100644 index 00000000000000..0485e80e906c86 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English norbert2_sentiment_norec_2 BertForSequenceClassification from NTCAL +author: John Snow Labs +name: norbert2_sentiment_norec_2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norbert2_sentiment_norec_2` is a English model originally trained by NTCAL. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_2_en_5.1.4_3.4_1698233003739.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_2_en_5.1.4_3.4_1698233003739.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec_2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec_2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norbert2_sentiment_norec_2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/NTCAL/norbert2_sentiment_norec_2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_4_en.md b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_4_en.md new file mode 100644 index 00000000000000..f7cec3abb9b5ee --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_4_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English norbert2_sentiment_norec_4 BertForSequenceClassification from NTCAL +author: John Snow Labs +name: norbert2_sentiment_norec_4 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norbert2_sentiment_norec_4` is a English model originally trained by NTCAL. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_4_en_5.1.4_3.4_1698235996431.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_4_en_5.1.4_3.4_1698235996431.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec_4","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec_4","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norbert2_sentiment_norec_4| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/NTCAL/norbert2_sentiment_norec_4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_6_en.md b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_6_en.md new file mode 100644 index 00000000000000..60212355c661b3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_6_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English norbert2_sentiment_norec_6 BertForSequenceClassification from NTCAL +author: John Snow Labs +name: norbert2_sentiment_norec_6 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norbert2_sentiment_norec_6` is a English model originally trained by NTCAL. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_6_en_5.1.4_3.4_1698237683293.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_6_en_5.1.4_3.4_1698237683293.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec_6","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec_6","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norbert2_sentiment_norec_6| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/NTCAL/norbert2_sentiment_norec_6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_7_en.md b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_7_en.md new file mode 100644 index 00000000000000..1927f729a20ea6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_7_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English norbert2_sentiment_norec_7 BertForSequenceClassification from NTCAL +author: John Snow Labs +name: norbert2_sentiment_norec_7 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norbert2_sentiment_norec_7` is a English model originally trained by NTCAL. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_7_en_5.1.4_3.4_1698239342573.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_7_en_5.1.4_3.4_1698239342573.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec_7","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec_7","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norbert2_sentiment_norec_7| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/NTCAL/norbert2_sentiment_norec_7 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_8_en.md b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_8_en.md new file mode 100644 index 00000000000000..fe27aa1b1fce53 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English norbert2_sentiment_norec_8 BertForSequenceClassification from NTCAL +author: John Snow Labs +name: norbert2_sentiment_norec_8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norbert2_sentiment_norec_8` is a English model originally trained by NTCAL. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_8_en_5.1.4_3.4_1698244059994.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_8_en_5.1.4_3.4_1698244059994.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec_8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec_8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norbert2_sentiment_norec_8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/NTCAL/norbert2_sentiment_norec_8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_9_en.md b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_9_en.md new file mode 100644 index 00000000000000..13708009c12d63 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_9_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English norbert2_sentiment_norec_9 BertForSequenceClassification from NTCAL +author: John Snow Labs +name: norbert2_sentiment_norec_9 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norbert2_sentiment_norec_9` is a English model originally trained by NTCAL. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_9_en_5.1.4_3.4_1698245023007.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_9_en_5.1.4_3.4_1698245023007.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec_9","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec_9","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norbert2_sentiment_norec_9| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|467.4 MB| + +## References + +https://huggingface.co/NTCAL/norbert2_sentiment_norec_9 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_no.md b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_no.md new file mode 100644 index 00000000000000..4856cf5837f5a6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_no.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Norwegian norbert2_sentiment_norec BertForSequenceClassification from NTCAL +author: John Snow Labs +name: norbert2_sentiment_norec +date: 2023-10-25 +tags: [bert, "no", open_source, sequence_classification, onnx] +task: Text Classification +language: "no" +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norbert2_sentiment_norec` is a Norwegian model originally trained by NTCAL. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_no_5.1.4_3.4_1698195161375.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_no_5.1.4_3.4_1698195161375.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec","no")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec","no") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norbert2_sentiment_norec| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|no| +|Size:|467.4 MB| + +## References + +https://huggingface.co/NTCAL/norbert2_sentiment_norec \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_tonga_tonga_islands_gpu_3000_rader_en.md b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_tonga_tonga_islands_gpu_3000_rader_en.md new file mode 100644 index 00000000000000..f435fc28bb4ba9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-norbert2_sentiment_norec_tonga_tonga_islands_gpu_3000_rader_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English norbert2_sentiment_norec_tonga_tonga_islands_gpu_3000_rader BertForSequenceClassification from NTCAL +author: John Snow Labs +name: norbert2_sentiment_norec_tonga_tonga_islands_gpu_3000_rader +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norbert2_sentiment_norec_tonga_tonga_islands_gpu_3000_rader` is a English model originally trained by NTCAL. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_tonga_tonga_islands_gpu_3000_rader_en_5.1.4_3.4_1698276445338.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norbert2_sentiment_norec_tonga_tonga_islands_gpu_3000_rader_en_5.1.4_3.4_1698276445338.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec_tonga_tonga_islands_gpu_3000_rader","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("norbert2_sentiment_norec_tonga_tonga_islands_gpu_3000_rader","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norbert2_sentiment_norec_tonga_tonga_islands_gpu_3000_rader| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/NTCAL/norbert2_sentiment_norec_to_gpu_3000_rader \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-norsk_bert_fintuned_en.md b/docs/_posts/ahmedlone127/2023-10-25-norsk_bert_fintuned_en.md new file mode 100644 index 00000000000000..840c67aedb048e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-norsk_bert_fintuned_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English norsk_bert_fintuned BertForSequenceClassification from kirisums +author: John Snow Labs +name: norsk_bert_fintuned +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`norsk_bert_fintuned` is a English model originally trained by kirisums. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/norsk_bert_fintuned_en_5.1.4_3.4_1698224676169.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/norsk_bert_fintuned_en_5.1.4_3.4_1698224676169.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("norsk_bert_fintuned","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("norsk_bert_fintuned","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|norsk_bert_fintuned| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|668.4 MB| + +## References + +https://huggingface.co/kirisums/norsk-bert-fintuned \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-northern_sami_bert_en.md b/docs/_posts/ahmedlone127/2023-10-25-northern_sami_bert_en.md new file mode 100644 index 00000000000000..f406ec79495580 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-northern_sami_bert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English northern_sami_bert BertForSequenceClassification from thearod5 +author: John Snow Labs +name: northern_sami_bert +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`northern_sami_bert` is a English model originally trained by thearod5. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/northern_sami_bert_en_5.1.4_3.4_1698201246750.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/northern_sami_bert_en_5.1.4_3.4_1698201246750.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("northern_sami_bert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("northern_sami_bert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|northern_sami_bert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/thearod5/se-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-nosql_identifier_bert_en.md b/docs/_posts/ahmedlone127/2023-10-25-nosql_identifier_bert_en.md new file mode 100644 index 00000000000000..58a0b5fabc99ea --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-nosql_identifier_bert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English nosql_identifier_bert BertForSequenceClassification from ankush-003 +author: John Snow Labs +name: nosql_identifier_bert +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`nosql_identifier_bert` is a English model originally trained by ankush-003. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/nosql_identifier_bert_en_5.1.4_3.4_1698201204944.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/nosql_identifier_bert_en_5.1.4_3.4_1698201204944.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("nosql_identifier_bert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("nosql_identifier_bert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|nosql_identifier_bert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ankush-003/nosql-identifier-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-ogbv_gender_bert_hindi_english_hasoc20a_fin_en.md b/docs/_posts/ahmedlone127/2023-10-25-ogbv_gender_bert_hindi_english_hasoc20a_fin_en.md new file mode 100644 index 00000000000000..0cadc0726cfaa2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-ogbv_gender_bert_hindi_english_hasoc20a_fin_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English ogbv_gender_bert_hindi_english_hasoc20a_fin BertForSequenceClassification from Maha +author: John Snow Labs +name: ogbv_gender_bert_hindi_english_hasoc20a_fin +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ogbv_gender_bert_hindi_english_hasoc20a_fin` is a English model originally trained by Maha. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ogbv_gender_bert_hindi_english_hasoc20a_fin_en_5.1.4_3.4_1698224066734.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ogbv_gender_bert_hindi_english_hasoc20a_fin_en_5.1.4_3.4_1698224066734.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("ogbv_gender_bert_hindi_english_hasoc20a_fin","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("ogbv_gender_bert_hindi_english_hasoc20a_fin","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ogbv_gender_bert_hindi_english_hasoc20a_fin| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|667.3 MB| + +## References + +https://huggingface.co/Maha/OGBV-gender-bert-hi-en-hasoc20a-fin \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-pipp_finder_bert_base_cased_en.md b/docs/_posts/ahmedlone127/2023-10-25-pipp_finder_bert_base_cased_en.md new file mode 100644 index 00000000000000..2ce48d13b73d85 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-pipp_finder_bert_base_cased_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English pipp_finder_bert_base_cased BertForSequenceClassification from cgpotts +author: John Snow Labs +name: pipp_finder_bert_base_cased +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`pipp_finder_bert_base_cased` is a English model originally trained by cgpotts. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/pipp_finder_bert_base_cased_en_5.1.4_3.4_1698220093324.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/pipp_finder_bert_base_cased_en_5.1.4_3.4_1698220093324.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("pipp_finder_bert_base_cased","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("pipp_finder_bert_base_cased","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|pipp_finder_bert_base_cased| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/cgpotts/pipp-finder-bert-base-cased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-platzi_distilroberta_base_mrpc_glue_en.md b/docs/_posts/ahmedlone127/2023-10-25-platzi_distilroberta_base_mrpc_glue_en.md new file mode 100644 index 00000000000000..af3b8ce66b0268 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-platzi_distilroberta_base_mrpc_glue_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English platzi_distilroberta_base_mrpc_glue BertForSequenceClassification from eormeno12 +author: John Snow Labs +name: platzi_distilroberta_base_mrpc_glue +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`platzi_distilroberta_base_mrpc_glue` is a English model originally trained by eormeno12. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/platzi_distilroberta_base_mrpc_glue_en_5.1.4_3.4_1698201428077.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/platzi_distilroberta_base_mrpc_glue_en_5.1.4_3.4_1698201428077.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("platzi_distilroberta_base_mrpc_glue","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("platzi_distilroberta_base_mrpc_glue","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|platzi_distilroberta_base_mrpc_glue| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/eormeno12/platzi-distilroberta-base-mrpc-glue \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-prot_bert_finetuned_localization_hazel0707_en.md b/docs/_posts/ahmedlone127/2023-10-25-prot_bert_finetuned_localization_hazel0707_en.md new file mode 100644 index 00000000000000..f004e6767bc5be --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-prot_bert_finetuned_localization_hazel0707_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English prot_bert_finetuned_localization_hazel0707 BertForSequenceClassification from Hazel0707 +author: John Snow Labs +name: prot_bert_finetuned_localization_hazel0707 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`prot_bert_finetuned_localization_hazel0707` is a English model originally trained by Hazel0707. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/prot_bert_finetuned_localization_hazel0707_en_5.1.4_3.4_1698205163369.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/prot_bert_finetuned_localization_hazel0707_en_5.1.4_3.4_1698205163369.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("prot_bert_finetuned_localization_hazel0707","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("prot_bert_finetuned_localization_hazel0707","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|prot_bert_finetuned_localization_hazel0707| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/Hazel0707/prot_bert-finetuned-localization \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-roberta_fake_real_en.md b/docs/_posts/ahmedlone127/2023-10-25-roberta_fake_real_en.md new file mode 100644 index 00000000000000..ff3001149544cc --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-roberta_fake_real_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English roberta_fake_real BertForSequenceClassification from PravallikaMyneni +author: John Snow Labs +name: roberta_fake_real +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`roberta_fake_real` is a English model originally trained by PravallikaMyneni. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/roberta_fake_real_en_5.1.4_3.4_1698221775747.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/roberta_fake_real_en_5.1.4_3.4_1698221775747.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("roberta_fake_real","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("roberta_fake_real","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|roberta_fake_real| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/PravallikaMyneni/roberta_fake_real \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-rubert_base_cased_conversational_paraphrase_v1_ru.md b/docs/_posts/ahmedlone127/2023-10-25-rubert_base_cased_conversational_paraphrase_v1_ru.md new file mode 100644 index 00000000000000..20b94c1925c599 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-rubert_base_cased_conversational_paraphrase_v1_ru.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Russian rubert_base_cased_conversational_paraphrase_v1 BertForSequenceClassification from s-nlp +author: John Snow Labs +name: rubert_base_cased_conversational_paraphrase_v1 +date: 2023-10-25 +tags: [bert, ru, open_source, sequence_classification, onnx] +task: Text Classification +language: ru +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_base_cased_conversational_paraphrase_v1` is a Russian model originally trained by s-nlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_base_cased_conversational_paraphrase_v1_ru_5.1.4_3.4_1698270052372.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_base_cased_conversational_paraphrase_v1_ru_5.1.4_3.4_1698270052372.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("rubert_base_cased_conversational_paraphrase_v1","ru")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("rubert_base_cased_conversational_paraphrase_v1","ru") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rubert_base_cased_conversational_paraphrase_v1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|ru| +|Size:|664.4 MB| + +## References + +https://huggingface.co/s-nlp/rubert-base-cased-conversational-paraphrase-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-rubert_base_cased_sentiment_nepal_bhasa_ru.md b/docs/_posts/ahmedlone127/2023-10-25-rubert_base_cased_sentiment_nepal_bhasa_ru.md new file mode 100644 index 00000000000000..870674ec46887d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-rubert_base_cased_sentiment_nepal_bhasa_ru.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Russian rubert_base_cased_sentiment_nepal_bhasa BertForSequenceClassification from MonoHime +author: John Snow Labs +name: rubert_base_cased_sentiment_nepal_bhasa +date: 2023-10-25 +tags: [bert, ru, open_source, sequence_classification, onnx] +task: Text Classification +language: ru +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_base_cased_sentiment_nepal_bhasa` is a Russian model originally trained by MonoHime. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_base_cased_sentiment_nepal_bhasa_ru_5.1.4_3.4_1698251812853.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_base_cased_sentiment_nepal_bhasa_ru_5.1.4_3.4_1698251812853.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("rubert_base_cased_sentiment_nepal_bhasa","ru")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("rubert_base_cased_sentiment_nepal_bhasa","ru") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rubert_base_cased_sentiment_nepal_bhasa| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|ru| +|Size:|664.4 MB| + +## References + +https://huggingface.co/MonoHime/rubert-base-cased-sentiment-new \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-rubert_base_corruption_detector_ru.md b/docs/_posts/ahmedlone127/2023-10-25-rubert_base_corruption_detector_ru.md new file mode 100644 index 00000000000000..87c0dc0b65bf61 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-rubert_base_corruption_detector_ru.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Russian rubert_base_corruption_detector BertForSequenceClassification from s-nlp +author: John Snow Labs +name: rubert_base_corruption_detector +date: 2023-10-25 +tags: [bert, ru, open_source, sequence_classification, onnx] +task: Text Classification +language: ru +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_base_corruption_detector` is a Russian model originally trained by s-nlp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_base_corruption_detector_ru_5.1.4_3.4_1698248343247.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_base_corruption_detector_ru_5.1.4_3.4_1698248343247.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("rubert_base_corruption_detector","ru")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("rubert_base_corruption_detector","ru") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rubert_base_corruption_detector| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|ru| +|Size:|666.5 MB| + +## References + +https://huggingface.co/s-nlp/rubert-base-corruption-detector \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-rubert_base_emotion_russian_cedr_m7_en.md b/docs/_posts/ahmedlone127/2023-10-25-rubert_base_emotion_russian_cedr_m7_en.md new file mode 100644 index 00000000000000..2a9676fa5046d2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-rubert_base_emotion_russian_cedr_m7_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English rubert_base_emotion_russian_cedr_m7 BertForSequenceClassification from Aniemore +author: John Snow Labs +name: rubert_base_emotion_russian_cedr_m7 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_base_emotion_russian_cedr_m7` is a English model originally trained by Aniemore. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_base_emotion_russian_cedr_m7_en_5.1.4_3.4_1698207995037.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_base_emotion_russian_cedr_m7_en_5.1.4_3.4_1698207995037.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("rubert_base_emotion_russian_cedr_m7","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("rubert_base_emotion_russian_cedr_m7","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rubert_base_emotion_russian_cedr_m7| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|666.5 MB| + +## References + +https://huggingface.co/Aniemore/rubert-base-emotion-russian-cedr-m7 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-rubert_large_emotion_russian_cedr_m7_en.md b/docs/_posts/ahmedlone127/2023-10-25-rubert_large_emotion_russian_cedr_m7_en.md new file mode 100644 index 00000000000000..f9b4f7acf93a44 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-rubert_large_emotion_russian_cedr_m7_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English rubert_large_emotion_russian_cedr_m7 BertForSequenceClassification from Aniemore +author: John Snow Labs +name: rubert_large_emotion_russian_cedr_m7 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_large_emotion_russian_cedr_m7` is a English model originally trained by Aniemore. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_large_emotion_russian_cedr_m7_en_5.1.4_3.4_1698208388605.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_large_emotion_russian_cedr_m7_en_5.1.4_3.4_1698208388605.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("rubert_large_emotion_russian_cedr_m7","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("rubert_large_emotion_russian_cedr_m7","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rubert_large_emotion_russian_cedr_m7| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/Aniemore/rubert-large-emotion-russian-cedr-m7 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-rubert_rusentitweet_sismetanin_en.md b/docs/_posts/ahmedlone127/2023-10-25-rubert_rusentitweet_sismetanin_en.md new file mode 100644 index 00000000000000..e9f32b9b16863f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-rubert_rusentitweet_sismetanin_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English rubert_rusentitweet_sismetanin BertForSequenceClassification from sismetanin +author: John Snow Labs +name: rubert_rusentitweet_sismetanin +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_rusentitweet_sismetanin` is a English model originally trained by sismetanin. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_rusentitweet_sismetanin_en_5.1.4_3.4_1698243502522.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_rusentitweet_sismetanin_en_5.1.4_3.4_1698243502522.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("rubert_rusentitweet_sismetanin","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("rubert_rusentitweet_sismetanin","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rubert_rusentitweet_sismetanin| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|666.5 MB| + +## References + +https://huggingface.co/sismetanin/rubert-rusentitweet \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-rubert_sentence_mixin_en.md b/docs/_posts/ahmedlone127/2023-10-25-rubert_sentence_mixin_en.md new file mode 100644 index 00000000000000..328c4d67e30ce5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-rubert_sentence_mixin_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English rubert_sentence_mixin BertForSequenceClassification from OlegOrwell +author: John Snow Labs +name: rubert_sentence_mixin +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_sentence_mixin` is a English model originally trained by OlegOrwell. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_sentence_mixin_en_5.1.4_3.4_1698254334062.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_sentence_mixin_en_5.1.4_3.4_1698254334062.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("rubert_sentence_mixin","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("rubert_sentence_mixin","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rubert_sentence_mixin| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|666.5 MB| + +## References + +https://huggingface.co/OlegOrwell/rubert_sentence_mixin \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-rubert_tiny_emotion_russian_cedr_m7_en.md b/docs/_posts/ahmedlone127/2023-10-25-rubert_tiny_emotion_russian_cedr_m7_en.md new file mode 100644 index 00000000000000..9b2fd20f1d5a44 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-rubert_tiny_emotion_russian_cedr_m7_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English rubert_tiny_emotion_russian_cedr_m7 BertForSequenceClassification from Aniemore +author: John Snow Labs +name: rubert_tiny_emotion_russian_cedr_m7 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_tiny_emotion_russian_cedr_m7` is a English model originally trained by Aniemore. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_tiny_emotion_russian_cedr_m7_en_5.1.4_3.4_1698207727419.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_tiny_emotion_russian_cedr_m7_en_5.1.4_3.4_1698207727419.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("rubert_tiny_emotion_russian_cedr_m7","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("rubert_tiny_emotion_russian_cedr_m7","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rubert_tiny_emotion_russian_cedr_m7| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|109.5 MB| + +## References + +https://huggingface.co/Aniemore/rubert-tiny-emotion-russian-cedr-m7 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-rubert_tweetsentiment_en.md b/docs/_posts/ahmedlone127/2023-10-25-rubert_tweetsentiment_en.md new file mode 100644 index 00000000000000..f700d0e9809590 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-rubert_tweetsentiment_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English rubert_tweetsentiment BertForSequenceClassification from EMBEDDIA +author: John Snow Labs +name: rubert_tweetsentiment +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`rubert_tweetsentiment` is a English model originally trained by EMBEDDIA. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/rubert_tweetsentiment_en_5.1.4_3.4_1698202113288.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/rubert_tweetsentiment_en_5.1.4_3.4_1698202113288.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("rubert_tweetsentiment","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("rubert_tweetsentiment","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|rubert_tweetsentiment| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|666.5 MB| + +## References + +https://huggingface.co/EMBEDDIA/rubert-tweetsentiment \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-samyarn_bert_base_multilingual_cased_xx.md b/docs/_posts/ahmedlone127/2023-10-25-samyarn_bert_base_multilingual_cased_xx.md new file mode 100644 index 00000000000000..ea42b4ff0221b2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-samyarn_bert_base_multilingual_cased_xx.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Multilingual samyarn_bert_base_multilingual_cased BertForSequenceClassification from Kao +author: John Snow Labs +name: samyarn_bert_base_multilingual_cased +date: 2023-10-25 +tags: [bert, xx, open_source, sequence_classification, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`samyarn_bert_base_multilingual_cased` is a Multilingual model originally trained by Kao. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/samyarn_bert_base_multilingual_cased_xx_5.1.4_3.4_1698220388695.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/samyarn_bert_base_multilingual_cased_xx_5.1.4_3.4_1698220388695.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("samyarn_bert_base_multilingual_cased","xx")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("samyarn_bert_base_multilingual_cased","xx") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|samyarn_bert_base_multilingual_cased| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|667.3 MB| + +## References + +https://huggingface.co/Kao/samyarn-bert-base-multilingual-cased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-scibert_finetuned_dagpap22_en.md b/docs/_posts/ahmedlone127/2023-10-25-scibert_finetuned_dagpap22_en.md new file mode 100644 index 00000000000000..6232c4c3edc170 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-scibert_finetuned_dagpap22_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English scibert_finetuned_dagpap22 BertForSequenceClassification from domenicrosati +author: John Snow Labs +name: scibert_finetuned_dagpap22 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scibert_finetuned_dagpap22` is a English model originally trained by domenicrosati. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scibert_finetuned_dagpap22_en_5.1.4_3.4_1698211484008.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scibert_finetuned_dagpap22_en_5.1.4_3.4_1698211484008.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("scibert_finetuned_dagpap22","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("scibert_finetuned_dagpap22","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scibert_finetuned_dagpap22| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|412.2 MB| + +## References + +https://huggingface.co/domenicrosati/scibert-finetuned-DAGPap22 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-scibert_scivocab_uncased_ft_m3_lc_en.md b/docs/_posts/ahmedlone127/2023-10-25-scibert_scivocab_uncased_ft_m3_lc_en.md new file mode 100644 index 00000000000000..44e783f57fd124 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-scibert_scivocab_uncased_ft_m3_lc_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English scibert_scivocab_uncased_ft_m3_lc BertForSequenceClassification from sarahmiller137 +author: John Snow Labs +name: scibert_scivocab_uncased_ft_m3_lc +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scibert_scivocab_uncased_ft_m3_lc` is a English model originally trained by sarahmiller137. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scibert_scivocab_uncased_ft_m3_lc_en_5.1.4_3.4_1698266550136.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scibert_scivocab_uncased_ft_m3_lc_en_5.1.4_3.4_1698266550136.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("scibert_scivocab_uncased_ft_m3_lc","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("scibert_scivocab_uncased_ft_m3_lc","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scibert_scivocab_uncased_ft_m3_lc| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|412.2 MB| + +## References + +https://huggingface.co/sarahmiller137/scibert-scivocab-uncased-ft-m3-lc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-scotus_bert_chiragasarpota_en.md b/docs/_posts/ahmedlone127/2023-10-25-scotus_bert_chiragasarpota_en.md new file mode 100644 index 00000000000000..a10a1eec0a6f4c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-scotus_bert_chiragasarpota_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English scotus_bert_chiragasarpota BertForSequenceClassification from chiragasarpota +author: John Snow Labs +name: scotus_bert_chiragasarpota +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scotus_bert_chiragasarpota` is a English model originally trained by chiragasarpota. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scotus_bert_chiragasarpota_en_5.1.4_3.4_1698192913047.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scotus_bert_chiragasarpota_en_5.1.4_3.4_1698192913047.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("scotus_bert_chiragasarpota","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("scotus_bert_chiragasarpota","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scotus_bert_chiragasarpota| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/chiragasarpota/scotus-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-sena_finetuned_bert_en.md b/docs/_posts/ahmedlone127/2023-10-25-sena_finetuned_bert_en.md new file mode 100644 index 00000000000000..7db5bb803c9916 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-sena_finetuned_bert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English sena_finetuned_bert BertForSequenceClassification from snadsdmr +author: John Snow Labs +name: sena_finetuned_bert +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sena_finetuned_bert` is a English model originally trained by snadsdmr. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sena_finetuned_bert_en_5.1.4_3.4_1698250033431.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sena_finetuned_bert_en_5.1.4_3.4_1698250033431.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("sena_finetuned_bert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("sena_finetuned_bert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sena_finetuned_bert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/snadsdmr/sena_finetuned_bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-sentiment_hts2_hubert_hungarian_hu.md b/docs/_posts/ahmedlone127/2023-10-25-sentiment_hts2_hubert_hungarian_hu.md new file mode 100644 index 00000000000000..76fb842f567620 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-sentiment_hts2_hubert_hungarian_hu.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Hungarian sentiment_hts2_hubert_hungarian BertForSequenceClassification from NYTK +author: John Snow Labs +name: sentiment_hts2_hubert_hungarian +date: 2023-10-25 +tags: [bert, hu, open_source, sequence_classification, onnx] +task: Text Classification +language: hu +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_hts2_hubert_hungarian` is a Hungarian model originally trained by NYTK. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_hts2_hubert_hungarian_hu_5.1.4_3.4_1698227753323.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_hts2_hubert_hungarian_hu_5.1.4_3.4_1698227753323.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("sentiment_hts2_hubert_hungarian","hu")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("sentiment_hts2_hubert_hungarian","hu") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentiment_hts2_hubert_hungarian| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|hu| +|Size:|414.7 MB| + +## References + +https://huggingface.co/NYTK/sentiment-hts2-hubert-hungarian \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-sentiment_hts5_hubert_hungarian_hu.md b/docs/_posts/ahmedlone127/2023-10-25-sentiment_hts5_hubert_hungarian_hu.md new file mode 100644 index 00000000000000..025fc5dbefc631 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-sentiment_hts5_hubert_hungarian_hu.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Hungarian sentiment_hts5_hubert_hungarian BertForSequenceClassification from NYTK +author: John Snow Labs +name: sentiment_hts5_hubert_hungarian +date: 2023-10-25 +tags: [bert, hu, open_source, sequence_classification, onnx] +task: Text Classification +language: hu +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sentiment_hts5_hubert_hungarian` is a Hungarian model originally trained by NYTK. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sentiment_hts5_hubert_hungarian_hu_5.1.4_3.4_1698228545238.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sentiment_hts5_hubert_hungarian_hu_5.1.4_3.4_1698228545238.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("sentiment_hts5_hubert_hungarian","hu")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("sentiment_hts5_hubert_hungarian","hu") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sentiment_hts5_hubert_hungarian| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|hu| +|Size:|414.7 MB| + +## References + +https://huggingface.co/NYTK/sentiment-hts5-hubert-hungarian \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-sikubert_finetuned_poetry_en.md b/docs/_posts/ahmedlone127/2023-10-25-sikubert_finetuned_poetry_en.md new file mode 100644 index 00000000000000..24a66e93420267 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-sikubert_finetuned_poetry_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English sikubert_finetuned_poetry BertForSequenceClassification from synpjh +author: John Snow Labs +name: sikubert_finetuned_poetry +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sikubert_finetuned_poetry` is a English model originally trained by synpjh. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sikubert_finetuned_poetry_en_5.1.4_3.4_1698205521845.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sikubert_finetuned_poetry_en_5.1.4_3.4_1698205521845.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("sikubert_finetuned_poetry","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("sikubert_finetuned_poetry","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sikubert_finetuned_poetry| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|408.9 MB| + +## References + +https://huggingface.co/synpjh/sikubert-finetuned-poetry \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-solved_finbert_tone_en.md b/docs/_posts/ahmedlone127/2023-10-25-solved_finbert_tone_en.md new file mode 100644 index 00000000000000..7c6d502cfcf9f8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-solved_finbert_tone_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English solved_finbert_tone BertForSequenceClassification from ldeb +author: John Snow Labs +name: solved_finbert_tone +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`solved_finbert_tone` is a English model originally trained by ldeb. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/solved_finbert_tone_en_5.1.4_3.4_1698211497295.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/solved_finbert_tone_en_5.1.4_3.4_1698211497295.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("solved_finbert_tone","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("solved_finbert_tone","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|solved_finbert_tone| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.6 MB| + +## References + +https://huggingface.co/ldeb/solved-finbert-tone \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-sqlclassification_normal_bert_model_en.md b/docs/_posts/ahmedlone127/2023-10-25-sqlclassification_normal_bert_model_en.md new file mode 100644 index 00000000000000..e19b3a5eb70245 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-sqlclassification_normal_bert_model_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English sqlclassification_normal_bert_model BertForSequenceClassification from flagship +author: John Snow Labs +name: sqlclassification_normal_bert_model +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`sqlclassification_normal_bert_model` is a English model originally trained by flagship. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/sqlclassification_normal_bert_model_en_5.1.4_3.4_1698214173523.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/sqlclassification_normal_bert_model_en_5.1.4_3.4_1698214173523.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("sqlclassification_normal_bert_model","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("sqlclassification_normal_bert_model","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|sqlclassification_normal_bert_model| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/flagship/sqlclassification_normal_bert_model \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_0_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_0_en.md new file mode 100644 index 00000000000000..1adcc9b6675ed6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_0_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_0 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_0 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_0` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_0_en_5.1.4_3.4_1698194100114.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_0_en_5.1.4_3.4_1698194100114.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_0","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_0","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_0| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-0 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_10_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_10_en.md new file mode 100644 index 00000000000000..fda2fb8a71d9d2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_10_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_10 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_10 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_10` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_10_en_5.1.4_3.4_1698204826153.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_10_en_5.1.4_3.4_1698204826153.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_10","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_10","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_10| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-10 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_11_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_11_en.md new file mode 100644 index 00000000000000..1a9a05034ea083 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_11_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_11 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_11 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_11` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_11_en_5.1.4_3.4_1698196289627.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_11_en_5.1.4_3.4_1698196289627.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_11","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_11","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_11| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-11 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_12_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_12_en.md new file mode 100644 index 00000000000000..f879298658eb0b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_12_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_12 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_12 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_12` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_12_en_5.1.4_3.4_1698202946217.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_12_en_5.1.4_3.4_1698202946217.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_12","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_12","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_12| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-12 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_13_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_13_en.md new file mode 100644 index 00000000000000..b04be0adf54361 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_13_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_13 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_13 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_13` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_13_en_5.1.4_3.4_1698202339295.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_13_en_5.1.4_3.4_1698202339295.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_13","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_13","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_13| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-13 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_14_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_14_en.md new file mode 100644 index 00000000000000..ce7c94f6764be6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_14_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_14 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_14 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_14` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_14_en_5.1.4_3.4_1698206251020.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_14_en_5.1.4_3.4_1698206251020.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_14","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_14","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_14| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-14 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_15_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_15_en.md new file mode 100644 index 00000000000000..d02e3d614c3282 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_15_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_15 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_15 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_15` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_15_en_5.1.4_3.4_1698201749425.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_15_en_5.1.4_3.4_1698201749425.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_15","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_15","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_15| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-15 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_16_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_16_en.md new file mode 100644 index 00000000000000..c0542f65b189d9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_16_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_16 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_16 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_16` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_16_en_5.1.4_3.4_1698202138259.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_16_en_5.1.4_3.4_1698202138259.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_16","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_16","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_16| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-16 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_17_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_17_en.md new file mode 100644 index 00000000000000..192f7fa3a0e8e2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_17_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_17 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_17 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_17` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_17_en_5.1.4_3.4_1698194512012.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_17_en_5.1.4_3.4_1698194512012.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_17","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_17","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_17| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-17 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_18_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_18_en.md new file mode 100644 index 00000000000000..0d1b09cef1df6a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_18_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_18 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_18 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_18` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_18_en_5.1.4_3.4_1698197910979.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_18_en_5.1.4_3.4_1698197910979.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_18","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_18","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_18| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-18 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_19_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_19_en.md new file mode 100644 index 00000000000000..74d8b69357ec03 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_19_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_19 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_19 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_19` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_19_en_5.1.4_3.4_1698193304132.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_19_en_5.1.4_3.4_1698193304132.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_19","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_19","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_19| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-19 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_1_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_1_en.md new file mode 100644 index 00000000000000..559b5f827c2a77 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_1_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_1 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_1 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_1` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_1_en_5.1.4_3.4_1698206917592.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_1_en_5.1.4_3.4_1698206917592.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_1","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_1","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_20_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_20_en.md new file mode 100644 index 00000000000000..6d3420e09b91ba --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_20_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_20 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_20 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_20` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_20_en_5.1.4_3.4_1698200494489.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_20_en_5.1.4_3.4_1698200494489.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_20","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_20","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_20| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-20 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_21_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_21_en.md new file mode 100644 index 00000000000000..1e462eeaaf5b43 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_21_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_21 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_21 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_21` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_21_en_5.1.4_3.4_1698206393610.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_21_en_5.1.4_3.4_1698206393610.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_21","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_21","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_21| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-21 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_22_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_22_en.md new file mode 100644 index 00000000000000..1b2bde12d799ff --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_22_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_22 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_22 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_22` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_22_en_5.1.4_3.4_1698194286917.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_22_en_5.1.4_3.4_1698194286917.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_22","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_22","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_22| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-22 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_23_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_23_en.md new file mode 100644 index 00000000000000..9c833232fcdc08 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_23_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_23 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_23 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_23` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_23_en_5.1.4_3.4_1698207111260.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_23_en_5.1.4_3.4_1698207111260.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_23","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_23","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_23| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-23 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_24_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_24_en.md new file mode 100644 index 00000000000000..17740e1a45d10c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_24_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_24 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_24 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_24` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_24_en_5.1.4_3.4_1698196718644.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_24_en_5.1.4_3.4_1698196718644.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_24","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_24","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_24| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-24 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_25_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_25_en.md new file mode 100644 index 00000000000000..4c15aea843aaa8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_25_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_25 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_25 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_25` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_25_en_5.1.4_3.4_1698207290480.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_25_en_5.1.4_3.4_1698207290480.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_25","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_25","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_25| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-25 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_26_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_26_en.md new file mode 100644 index 00000000000000..a894cc3daaaa75 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_26_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_26 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_26 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_26` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_26_en_5.1.4_3.4_1698195522947.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_26_en_5.1.4_3.4_1698195522947.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_26","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_26","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_26| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-26 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_27_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_27_en.md new file mode 100644 index 00000000000000..9158184da7520b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_27_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_27 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_27 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_27` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_27_en_5.1.4_3.4_1698201949807.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_27_en_5.1.4_3.4_1698201949807.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_27","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_27","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_27| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-27 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_28_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_28_en.md new file mode 100644 index 00000000000000..4519dba0ea4a0c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_28_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_28 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_28 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_28` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_28_en_5.1.4_3.4_1698194746151.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_28_en_5.1.4_3.4_1698194746151.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_28","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_28","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_28| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-28 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_29_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_29_en.md new file mode 100644 index 00000000000000..9dfaa454811515 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_29_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_29 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_29 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_29` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_29_en_5.1.4_3.4_1698195887691.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_29_en_5.1.4_3.4_1698195887691.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_29","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_29","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_29| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-29 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_2_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_2_en.md new file mode 100644 index 00000000000000..1cad5a9413a1bf --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_2 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_2 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_2` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_2_en_5.1.4_3.4_1698207970966.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_2_en_5.1.4_3.4_1698207970966.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_30_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_30_en.md new file mode 100644 index 00000000000000..2394c652a4f7b1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_30_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_30 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_30 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_30` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_30_en_5.1.4_3.4_1698195333470.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_30_en_5.1.4_3.4_1698195333470.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_30","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_30","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_30| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-30 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_31_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_31_en.md new file mode 100644 index 00000000000000..375545b18455f9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_31_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_31 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_31 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_31` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_31_en_5.1.4_3.4_1698205575224.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_31_en_5.1.4_3.4_1698205575224.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_31","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_31","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_31| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-31 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_32_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_32_en.md new file mode 100644 index 00000000000000..c1e0673254dd35 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_32_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_32 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_32 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_32` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_32_en_5.1.4_3.4_1698193896004.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_32_en_5.1.4_3.4_1698193896004.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_32","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_32","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_32| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-32 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_33_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_33_en.md new file mode 100644 index 00000000000000..7978abf4163fe3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_33_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_33 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_33 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_33` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_33_en_5.1.4_3.4_1698195707858.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_33_en_5.1.4_3.4_1698195707858.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_33","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_33","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_33| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-33 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_34_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_34_en.md new file mode 100644 index 00000000000000..042cdbaaa58d55 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_34_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_34 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_34 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_34` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_34_en_5.1.4_3.4_1698197715006.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_34_en_5.1.4_3.4_1698197715006.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_34","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_34","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_34| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-34 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_35_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_35_en.md new file mode 100644 index 00000000000000..b9a510c5c9e96e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_35_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_35 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_35 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_35` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_35_en_5.1.4_3.4_1698194923423.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_35_en_5.1.4_3.4_1698194923423.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_35","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_35","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_35| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-35 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_36_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_36_en.md new file mode 100644 index 00000000000000..b73e3d6d34f591 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_36_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_36 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_36 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_36` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_36_en_5.1.4_3.4_1698196482406.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_36_en_5.1.4_3.4_1698196482406.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_36","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_36","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_36| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-36 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_37_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_37_en.md new file mode 100644 index 00000000000000..f6a0972782f41f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_37_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_37 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_37 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_37` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_37_en_5.1.4_3.4_1698199974008.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_37_en_5.1.4_3.4_1698199974008.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_37","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_37","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_37| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-37 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_38_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_38_en.md new file mode 100644 index 00000000000000..d6b84a580a847c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_38_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_38 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_38 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_38` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_38_en_5.1.4_3.4_1698205728278.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_38_en_5.1.4_3.4_1698205728278.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_38","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_38","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_38| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-38 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_39_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_39_en.md new file mode 100644 index 00000000000000..39b71cf94deade --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_39_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_39 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_39 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_39` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_39_en_5.1.4_3.4_1698193524584.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_39_en_5.1.4_3.4_1698193524584.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_39","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_39","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_39| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-39 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_3_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_3_en.md new file mode 100644 index 00000000000000..e74293a7b63972 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_3_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_3 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_3 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_3` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_3_en_5.1.4_3.4_1698204625280.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_3_en_5.1.4_3.4_1698204625280.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_3","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_3","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_3| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_40_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_40_en.md new file mode 100644 index 00000000000000..8302ab3f592ff8 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_40_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_40 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_40 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_40` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_40_en_5.1.4_3.4_1698195158475.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_40_en_5.1.4_3.4_1698195158475.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_40","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_40","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_40| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-40 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_41_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_41_en.md new file mode 100644 index 00000000000000..cd5b58d034e15b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_41_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_41 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_41 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_41` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_41_en_5.1.4_3.4_1698206559892.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_41_en_5.1.4_3.4_1698206559892.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_41","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_41","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_41| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-41 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_42_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_42_en.md new file mode 100644 index 00000000000000..c3dcba2d3209a0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_42_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_42 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_42 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_42` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_42_en_5.1.4_3.4_1698199210250.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_42_en_5.1.4_3.4_1698199210250.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_42","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_42","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_42| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-42 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_43_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_43_en.md new file mode 100644 index 00000000000000..ba4088de428822 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_43_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_43 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_43 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_43` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_43_en_5.1.4_3.4_1698205039126.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_43_en_5.1.4_3.4_1698205039126.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_43","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_43","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_43| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-43 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_44_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_44_en.md new file mode 100644 index 00000000000000..c49008bbcfec3e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_44_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_44 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_44 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_44` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_44_en_5.1.4_3.4_1698196940511.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_44_en_5.1.4_3.4_1698196940511.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_44","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_44","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_44| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-44 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_45_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_45_en.md new file mode 100644 index 00000000000000..61d2b8627b0073 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_45_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_45 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_45 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_45` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_45_en_5.1.4_3.4_1698211090662.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_45_en_5.1.4_3.4_1698211090662.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_45","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_45","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_45| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-45 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_46_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_46_en.md new file mode 100644 index 00000000000000..33154a332d9539 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_46_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_46 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_46 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_46` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_46_en_5.1.4_3.4_1698197337466.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_46_en_5.1.4_3.4_1698197337466.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_46","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_46","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_46| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-46 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_47_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_47_en.md new file mode 100644 index 00000000000000..2ff186b1ad4dd4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_47_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_47 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_47 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_47` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_47_en_5.1.4_3.4_1698201157917.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_47_en_5.1.4_3.4_1698201157917.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_47","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_47","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_47| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-47 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_48_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_48_en.md new file mode 100644 index 00000000000000..eb7c32881ea6a1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_48_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_48 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_48 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_48` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_48_en_5.1.4_3.4_1698203742663.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_48_en_5.1.4_3.4_1698203742663.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_48","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_48","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_48| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-48 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_49_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_49_en.md new file mode 100644 index 00000000000000..2d67edd2064171 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_49_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_49 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_49 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_49` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_49_en_5.1.4_3.4_1698197139808.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_49_en_5.1.4_3.4_1698197139808.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_49","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_49","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_49| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-49 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_4_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_4_en.md new file mode 100644 index 00000000000000..f1c1d592762c6b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_4_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_4 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_4 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_4` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_4_en_5.1.4_3.4_1698193722580.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_4_en_5.1.4_3.4_1698193722580.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_4","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_4","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_4| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-4 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_50_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_50_en.md new file mode 100644 index 00000000000000..80e2a3d9f3af1b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_50_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_50 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_50 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_50` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_50_en_5.1.4_3.4_1698201549968.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_50_en_5.1.4_3.4_1698201549968.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_50","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_50","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_50| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-50 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_51_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_51_en.md new file mode 100644 index 00000000000000..76752fe8578b53 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_51_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_51 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_51 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_51` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_51_en_5.1.4_3.4_1698203578389.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_51_en_5.1.4_3.4_1698203578389.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_51","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_51","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_51| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-51 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_52_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_52_en.md new file mode 100644 index 00000000000000..6d6582a3874903 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_52_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_52 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_52 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_52` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_52_en_5.1.4_3.4_1698198979075.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_52_en_5.1.4_3.4_1698198979075.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_52","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_52","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_52| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-52 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_53_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_53_en.md new file mode 100644 index 00000000000000..d751eb41c5e1c0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_53_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_53 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_53 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_53` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_53_en_5.1.4_3.4_1698207734508.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_53_en_5.1.4_3.4_1698207734508.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_53","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_53","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_53| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-53 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_54_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_54_en.md new file mode 100644 index 00000000000000..7ae3210c157b6d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_54_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_54 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_54 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_54` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_54_en_5.1.4_3.4_1698205408269.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_54_en_5.1.4_3.4_1698205408269.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_54","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_54","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_54| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-54 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_55_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_55_en.md new file mode 100644 index 00000000000000..9a5baf9401f29b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_55_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_55 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_55 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_55` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_55_en_5.1.4_3.4_1698196108440.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_55_en_5.1.4_3.4_1698196108440.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_55","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_55","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_55| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-55 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_56_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_56_en.md new file mode 100644 index 00000000000000..2e46a4ebe5b8e3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_56_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_56 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_56 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_56` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_56_en_5.1.4_3.4_1698202740922.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_56_en_5.1.4_3.4_1698202740922.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_56","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_56","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_56| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-56 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_57_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_57_en.md new file mode 100644 index 00000000000000..75d27135e74a28 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_57_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_57 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_57 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_57` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_57_en_5.1.4_3.4_1698198595004.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_57_en_5.1.4_3.4_1698198595004.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_57","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_57","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_57| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-57 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_58_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_58_en.md new file mode 100644 index 00000000000000..dd7b8f1d51abc4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_58_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_58 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_58 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_58` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_58_en_5.1.4_3.4_1698200937531.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_58_en_5.1.4_3.4_1698200937531.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_58","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_58","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_58| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-58 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_59_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_59_en.md new file mode 100644 index 00000000000000..3b9abbbd5334ed --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_59_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_59 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_59 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_59` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_59_en_5.1.4_3.4_1698205221969.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_59_en_5.1.4_3.4_1698205221969.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_59","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_59","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_59| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-59 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_5_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_5_en.md new file mode 100644 index 00000000000000..3ed4e1111eaaa1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_5_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_5 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_5 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_5` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_5_en_5.1.4_3.4_1698203161321.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_5_en_5.1.4_3.4_1698203161321.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_5","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_5","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_5| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-5 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_60_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_60_en.md new file mode 100644 index 00000000000000..a609c4a7f55f95 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_60_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_60 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_60 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_60` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_60_en_5.1.4_3.4_1698201369330.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_60_en_5.1.4_3.4_1698201369330.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_60","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_60","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_60| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-60 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_61_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_61_en.md new file mode 100644 index 00000000000000..0f1d6d9d7993f5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_61_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_61 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_61 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_61` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_61_en_5.1.4_3.4_1698203921006.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_61_en_5.1.4_3.4_1698203921006.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_61","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_61","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_61| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-61 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_62_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_62_en.md new file mode 100644 index 00000000000000..2f78fd9098a28c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_62_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_62 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_62 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_62` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_62_en_5.1.4_3.4_1698204456665.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_62_en_5.1.4_3.4_1698204456665.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_62","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_62","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_62| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-62 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_63_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_63_en.md new file mode 100644 index 00000000000000..5035af9364286f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_63_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_63 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_63 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_63` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_63_en_5.1.4_3.4_1698200696666.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_63_en_5.1.4_3.4_1698200696666.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_63","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_63","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_63| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-63 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_64_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_64_en.md new file mode 100644 index 00000000000000..0c35026ebd6e86 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_64_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_64 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_64 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_64` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_64_en_5.1.4_3.4_1698205893853.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_64_en_5.1.4_3.4_1698205893853.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_64","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_64","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_64| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-64 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_65_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_65_en.md new file mode 100644 index 00000000000000..060b6d67371d9e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_65_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_65 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_65 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_65` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_65_en_5.1.4_3.4_1698198791587.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_65_en_5.1.4_3.4_1698198791587.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_65","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_65","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_65| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-65 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_66_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_66_en.md new file mode 100644 index 00000000000000..65a219b4a3f9ec --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_66_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_66 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_66 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_66` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_66_en_5.1.4_3.4_1698204114463.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_66_en_5.1.4_3.4_1698204114463.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_66","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_66","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_66| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-66 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_67_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_67_en.md new file mode 100644 index 00000000000000..155f6505e56aad --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_67_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_67 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_67 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_67` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_67_en_5.1.4_3.4_1698203354474.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_67_en_5.1.4_3.4_1698203354474.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_67","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_67","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_67| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-67 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_68_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_68_en.md new file mode 100644 index 00000000000000..18875852e3848e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_68_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_68 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_68 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_68` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_68_en_5.1.4_3.4_1698200320551.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_68_en_5.1.4_3.4_1698200320551.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_68","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_68","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_68| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-68 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_69_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_69_en.md new file mode 100644 index 00000000000000..93b4fb67e14519 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_69_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_69 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_69 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_69` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_69_en_5.1.4_3.4_1698198162433.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_69_en_5.1.4_3.4_1698198162433.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_69","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_69","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_69| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-69 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_6_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_6_en.md new file mode 100644 index 00000000000000..8b9b933e7c1716 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_6_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_6 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_6 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_6` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_6_en_5.1.4_3.4_1698200139565.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_6_en_5.1.4_3.4_1698200139565.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_6","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_6","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_6| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-6 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_70_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_70_en.md new file mode 100644 index 00000000000000..ab94bc213554e3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_70_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_70 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_70 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_70` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_70_en_5.1.4_3.4_1698199412068.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_70_en_5.1.4_3.4_1698199412068.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_70","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_70","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_70| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-70 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_71_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_71_en.md new file mode 100644 index 00000000000000..50333ab5f0cdc6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_71_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_71 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_71 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_71` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_71_en_5.1.4_3.4_1698204297121.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_71_en_5.1.4_3.4_1698204297121.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_71","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_71","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_71| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-71 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_72_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_72_en.md new file mode 100644 index 00000000000000..6dcb4251c24949 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_72_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_72 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_72 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_72` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_72_en_5.1.4_3.4_1698198386848.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_72_en_5.1.4_3.4_1698198386848.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_72","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_72","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_72| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-72 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_73_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_73_en.md new file mode 100644 index 00000000000000..bee46117f59f79 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_73_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_73 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_73 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_73` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_73_en_5.1.4_3.4_1698208395070.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_73_en_5.1.4_3.4_1698208395070.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_73","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_73","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_73| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-73 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_74_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_74_en.md new file mode 100644 index 00000000000000..efbf82564f6168 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_74_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_74 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_74 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_74` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_74_en_5.1.4_3.4_1698208587674.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_74_en_5.1.4_3.4_1698208587674.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_74","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_74","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_74| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-74 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_75_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_75_en.md new file mode 100644 index 00000000000000..fd59ebf063d91c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_75_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_75 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_75 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_75` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_75_en_5.1.4_3.4_1698208214707.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_75_en_5.1.4_3.4_1698208214707.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_75","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_75","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_75| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-75 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_76_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_76_en.md new file mode 100644 index 00000000000000..3e2d8848a452d1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_76_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_76 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_76 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_76` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_76_en_5.1.4_3.4_1698206767477.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_76_en_5.1.4_3.4_1698206767477.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_76","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_76","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_76| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-76 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_77_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_77_en.md new file mode 100644 index 00000000000000..01414a577a0a57 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_77_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_77 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_77 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_77` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_77_en_5.1.4_3.4_1698199785215.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_77_en_5.1.4_3.4_1698199785215.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_77","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_77","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_77| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-77 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_78_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_78_en.md new file mode 100644 index 00000000000000..f972186928014b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_78_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_78 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_78 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_78` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_78_en_5.1.4_3.4_1698206075918.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_78_en_5.1.4_3.4_1698206075918.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_78","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_78","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_78| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-78 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_79_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_79_en.md new file mode 100644 index 00000000000000..c4db1c974f4592 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_79_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_79 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_79 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_79` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_79_en_5.1.4_3.4_1698207537777.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_79_en_5.1.4_3.4_1698207537777.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_79","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_79","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_79| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-79 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_7_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_7_en.md new file mode 100644 index 00000000000000..55d6e9a94b6d0d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_7_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_7 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_7 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_7` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_7_en_5.1.4_3.4_1698202539959.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_7_en_5.1.4_3.4_1698202539959.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_7","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_7","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_7| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-7 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_8_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_8_en.md new file mode 100644 index 00000000000000..a3e3388d1bb7d4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_8 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_8 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_8` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_8_en_5.1.4_3.4_1698197524932.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_8_en_5.1.4_3.4_1698197524932.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_9_en.md b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_9_en.md new file mode 100644 index 00000000000000..310e2cf7c7afc3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-std_0pnt2_bert_ft_cola_9_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English std_0pnt2_bert_ft_cola_9 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: std_0pnt2_bert_ft_cola_9 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`std_0pnt2_bert_ft_cola_9` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_9_en_5.1.4_3.4_1698199592174.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/std_0pnt2_bert_ft_cola_9_en_5.1.4_3.4_1698199592174.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_9","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("std_0pnt2_bert_ft_cola_9","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|std_0pnt2_bert_ft_cola_9| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/std_0pnt2_bert_ft_cola-9 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-subsimulator_bert_en.md b/docs/_posts/ahmedlone127/2023-10-25-subsimulator_bert_en.md new file mode 100644 index 00000000000000..6a05cde2f2cb9d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-subsimulator_bert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English subsimulator_bert BertForSequenceClassification from helliun +author: John Snow Labs +name: subsimulator_bert +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`subsimulator_bert` is a English model originally trained by helliun. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/subsimulator_bert_en_5.1.4_3.4_1698210463463.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/subsimulator_bert_en_5.1.4_3.4_1698210463463.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("subsimulator_bert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("subsimulator_bert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|subsimulator_bert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/helliun/subsimulator-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-swmh4_bert_en.md b/docs/_posts/ahmedlone127/2023-10-25-swmh4_bert_en.md new file mode 100644 index 00000000000000..c950024b9295e4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-swmh4_bert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English swmh4_bert BertForSequenceClassification from tiya1012 +author: John Snow Labs +name: swmh4_bert +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`swmh4_bert` is a English model originally trained by tiya1012. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/swmh4_bert_en_5.1.4_3.4_1698197603467.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/swmh4_bert_en_5.1.4_3.4_1698197603467.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("swmh4_bert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("swmh4_bert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|swmh4_bert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/tiya1012/swmh4_bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-symps_disease_bert_v3_c41_en.md b/docs/_posts/ahmedlone127/2023-10-25-symps_disease_bert_v3_c41_en.md new file mode 100644 index 00000000000000..4b534cb4cecd19 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-symps_disease_bert_v3_c41_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English symps_disease_bert_v3_c41 BertForSequenceClassification from shanover +author: John Snow Labs +name: symps_disease_bert_v3_c41 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`symps_disease_bert_v3_c41` is a English model originally trained by shanover. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/symps_disease_bert_v3_c41_en_5.1.4_3.4_1698193526004.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/symps_disease_bert_v3_c41_en_5.1.4_3.4_1698193526004.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("symps_disease_bert_v3_c41","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("symps_disease_bert_v3_c41","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|symps_disease_bert_v3_c41| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.5 MB| + +## References + +https://huggingface.co/shanover/symps_disease_bert_v3_c41 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-task_implicit_task__model_bert__aug_method_gm_en.md b/docs/_posts/ahmedlone127/2023-10-25-task_implicit_task__model_bert__aug_method_gm_en.md new file mode 100644 index 00000000000000..aba81338430b9b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-task_implicit_task__model_bert__aug_method_gm_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English task_implicit_task__model_bert__aug_method_gm BertForSequenceClassification from BenjaminOcampo +author: John Snow Labs +name: task_implicit_task__model_bert__aug_method_gm +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`task_implicit_task__model_bert__aug_method_gm` is a English model originally trained by BenjaminOcampo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/task_implicit_task__model_bert__aug_method_gm_en_5.1.4_3.4_1698196152482.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/task_implicit_task__model_bert__aug_method_gm_en_5.1.4_3.4_1698196152482.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("task_implicit_task__model_bert__aug_method_gm","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("task_implicit_task__model_bert__aug_method_gm","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|task_implicit_task__model_bert__aug_method_gm| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/BenjaminOcampo/task-implicit_task__model-bert__aug_method-gm \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-task_implicit_task__model_bert__aug_method_ra_en.md b/docs/_posts/ahmedlone127/2023-10-25-task_implicit_task__model_bert__aug_method_ra_en.md new file mode 100644 index 00000000000000..3e5c83db481921 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-task_implicit_task__model_bert__aug_method_ra_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English task_implicit_task__model_bert__aug_method_ra BertForSequenceClassification from BenjaminOcampo +author: John Snow Labs +name: task_implicit_task__model_bert__aug_method_ra +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`task_implicit_task__model_bert__aug_method_ra` is a English model originally trained by BenjaminOcampo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/task_implicit_task__model_bert__aug_method_ra_en_5.1.4_3.4_1698196596903.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/task_implicit_task__model_bert__aug_method_ra_en_5.1.4_3.4_1698196596903.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("task_implicit_task__model_bert__aug_method_ra","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("task_implicit_task__model_bert__aug_method_ra","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|task_implicit_task__model_bert__aug_method_ra| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/BenjaminOcampo/task-implicit_task__model-bert__aug_method-ra \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-task_subtle_task__model_bert__aug_method_gm_en.md b/docs/_posts/ahmedlone127/2023-10-25-task_subtle_task__model_bert__aug_method_gm_en.md new file mode 100644 index 00000000000000..3502876f9532ad --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-task_subtle_task__model_bert__aug_method_gm_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English task_subtle_task__model_bert__aug_method_gm BertForSequenceClassification from BenjaminOcampo +author: John Snow Labs +name: task_subtle_task__model_bert__aug_method_gm +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`task_subtle_task__model_bert__aug_method_gm` is a English model originally trained by BenjaminOcampo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/task_subtle_task__model_bert__aug_method_gm_en_5.1.4_3.4_1698196330798.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/task_subtle_task__model_bert__aug_method_gm_en_5.1.4_3.4_1698196330798.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("task_subtle_task__model_bert__aug_method_gm","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("task_subtle_task__model_bert__aug_method_gm","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|task_subtle_task__model_bert__aug_method_gm| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/BenjaminOcampo/task-subtle_task__model-bert__aug_method-gm \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-test_bert_training_en.md b/docs/_posts/ahmedlone127/2023-10-25-test_bert_training_en.md new file mode 100644 index 00000000000000..42d708d76199ca --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-test_bert_training_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English test_bert_training BertForSequenceClassification from andfanilo +author: John Snow Labs +name: test_bert_training +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`test_bert_training` is a English model originally trained by andfanilo. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/test_bert_training_en_5.1.4_3.4_1698209381719.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/test_bert_training_en_5.1.4_3.4_1698209381719.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("test_bert_training","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("test_bert_training","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|test_bert_training| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/andfanilo/test-bert-training \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-thermo_predictor_thermo_evotuning_prot_bert_en.md b/docs/_posts/ahmedlone127/2023-10-25-thermo_predictor_thermo_evotuning_prot_bert_en.md new file mode 100644 index 00000000000000..614435197e4c67 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-thermo_predictor_thermo_evotuning_prot_bert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English thermo_predictor_thermo_evotuning_prot_bert BertForSequenceClassification from cradle-bio +author: John Snow Labs +name: thermo_predictor_thermo_evotuning_prot_bert +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`thermo_predictor_thermo_evotuning_prot_bert` is a English model originally trained by cradle-bio. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/thermo_predictor_thermo_evotuning_prot_bert_en_5.1.4_3.4_1698201988248.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/thermo_predictor_thermo_evotuning_prot_bert_en_5.1.4_3.4_1698201988248.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("thermo_predictor_thermo_evotuning_prot_bert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("thermo_predictor_thermo_evotuning_prot_bert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|thermo_predictor_thermo_evotuning_prot_bert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.6 GB| + +## References + +https://huggingface.co/cradle-bio/thermo-predictor-thermo-evotuning-prot_bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_cola_distilled_en.md b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_cola_distilled_en.md new file mode 100644 index 00000000000000..1d11bd5e37be49 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_cola_distilled_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tiny_bert_cola_distilled BertForSequenceClassification from Sayan01 +author: John Snow Labs +name: tiny_bert_cola_distilled +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_cola_distilled` is a English model originally trained by Sayan01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_cola_distilled_en_5.1.4_3.4_1698192433149.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_cola_distilled_en_5.1.4_3.4_1698192433149.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_cola_distilled","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_cola_distilled","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_cola_distilled| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|54.2 MB| + +## References + +https://huggingface.co/Sayan01/tiny-bert-cola-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_mnli_distilled_en.md b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_mnli_distilled_en.md new file mode 100644 index 00000000000000..f965b0939d9eeb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_mnli_distilled_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tiny_bert_mnli_distilled BertForSequenceClassification from Sayan01 +author: John Snow Labs +name: tiny_bert_mnli_distilled +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_mnli_distilled` is a English model originally trained by Sayan01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_mnli_distilled_en_5.1.4_3.4_1698208686168.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_mnli_distilled_en_5.1.4_3.4_1698208686168.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_mnli_distilled","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_mnli_distilled","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_mnli_distilled| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/Sayan01/tiny-bert-mnli-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_mnli_m_distilled_en.md b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_mnli_m_distilled_en.md new file mode 100644 index 00000000000000..06c2eb7b1fe359 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_mnli_m_distilled_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tiny_bert_mnli_m_distilled BertForSequenceClassification from Sayan01 +author: John Snow Labs +name: tiny_bert_mnli_m_distilled +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_mnli_m_distilled` is a English model originally trained by Sayan01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_mnli_m_distilled_en_5.1.4_3.4_1698265199430.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_mnli_m_distilled_en_5.1.4_3.4_1698265199430.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_mnli_m_distilled","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_mnli_m_distilled","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_mnli_m_distilled| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|54.2 MB| + +## References + +https://huggingface.co/Sayan01/tiny-bert-mnli-m-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_mnli_mm_distilled_en.md b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_mnli_mm_distilled_en.md new file mode 100644 index 00000000000000..3475fe4bb0b79a --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_mnli_mm_distilled_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tiny_bert_mnli_mm_distilled BertForSequenceClassification from Sayan01 +author: John Snow Labs +name: tiny_bert_mnli_mm_distilled +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_mnli_mm_distilled` is a English model originally trained by Sayan01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_mnli_mm_distilled_en_5.1.4_3.4_1698268786072.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_mnli_mm_distilled_en_5.1.4_3.4_1698268786072.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_mnli_mm_distilled","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_mnli_mm_distilled","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_mnli_mm_distilled| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|54.2 MB| + +## References + +https://huggingface.co/Sayan01/tiny-bert-mnli-mm-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_mrpc_distilled_en.md b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_mrpc_distilled_en.md new file mode 100644 index 00000000000000..80a136cb63b766 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_mrpc_distilled_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tiny_bert_mrpc_distilled BertForSequenceClassification from Sayan01 +author: John Snow Labs +name: tiny_bert_mrpc_distilled +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_mrpc_distilled` is a English model originally trained by Sayan01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_mrpc_distilled_en_5.1.4_3.4_1698209972204.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_mrpc_distilled_en_5.1.4_3.4_1698209972204.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_mrpc_distilled","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_mrpc_distilled","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_mrpc_distilled| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|54.2 MB| + +## References + +https://huggingface.co/Sayan01/tiny-bert-mrpc-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_qnli_distilled_en.md b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_qnli_distilled_en.md new file mode 100644 index 00000000000000..5bf40203bc9d4e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_qnli_distilled_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tiny_bert_qnli_distilled BertForSequenceClassification from Sayan01 +author: John Snow Labs +name: tiny_bert_qnli_distilled +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_qnli_distilled` is a English model originally trained by Sayan01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_qnli_distilled_en_5.1.4_3.4_1698211808577.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_qnli_distilled_en_5.1.4_3.4_1698211808577.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_qnli_distilled","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_qnli_distilled","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_qnli_distilled| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|54.2 MB| + +## References + +https://huggingface.co/Sayan01/tiny-bert-qnli-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_qqp_128_distilled_en.md b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_qqp_128_distilled_en.md new file mode 100644 index 00000000000000..dddb665505352f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_qqp_128_distilled_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tiny_bert_qqp_128_distilled BertForSequenceClassification from Sayan01 +author: John Snow Labs +name: tiny_bert_qqp_128_distilled +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_qqp_128_distilled` is a English model originally trained by Sayan01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_qqp_128_distilled_en_5.1.4_3.4_1698273521563.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_qqp_128_distilled_en_5.1.4_3.4_1698273521563.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_qqp_128_distilled","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_qqp_128_distilled","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_qqp_128_distilled| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/Sayan01/tiny-bert-qqp-128-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_rte_distilled_en.md b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_rte_distilled_en.md new file mode 100644 index 00000000000000..a146a48ddc0f31 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_rte_distilled_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tiny_bert_rte_distilled BertForSequenceClassification from Sayan01 +author: John Snow Labs +name: tiny_bert_rte_distilled +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_rte_distilled` is a English model originally trained by Sayan01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_rte_distilled_en_5.1.4_3.4_1698210066696.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_rte_distilled_en_5.1.4_3.4_1698210066696.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_rte_distilled","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_rte_distilled","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_rte_distilled| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|54.2 MB| + +## References + +https://huggingface.co/Sayan01/tiny-bert-rte-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_sst2_distilled_kaakekhan_en.md b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_sst2_distilled_kaakekhan_en.md new file mode 100644 index 00000000000000..bd625d12052856 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_sst2_distilled_kaakekhan_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tiny_bert_sst2_distilled_kaakekhan BertForSequenceClassification from kaakekhan +author: John Snow Labs +name: tiny_bert_sst2_distilled_kaakekhan +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_sst2_distilled_kaakekhan` is a English model originally trained by kaakekhan. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_sst2_distilled_kaakekhan_en_5.1.4_3.4_1698203758116.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_sst2_distilled_kaakekhan_en_5.1.4_3.4_1698203758116.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_sst2_distilled_kaakekhan","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_sst2_distilled_kaakekhan","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_sst2_distilled_kaakekhan| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/kaakekhan/tiny-bert-sst2-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_sst2_distilled_kaitlineryan99_en.md b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_sst2_distilled_kaitlineryan99_en.md new file mode 100644 index 00000000000000..fc7210108e04e5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_sst2_distilled_kaitlineryan99_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tiny_bert_sst2_distilled_kaitlineryan99 BertForSequenceClassification from kaitlineryan99 +author: John Snow Labs +name: tiny_bert_sst2_distilled_kaitlineryan99 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_sst2_distilled_kaitlineryan99` is a English model originally trained by kaitlineryan99. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_sst2_distilled_kaitlineryan99_en_5.1.4_3.4_1698270563429.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_sst2_distilled_kaitlineryan99_en_5.1.4_3.4_1698270563429.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_sst2_distilled_kaitlineryan99","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_sst2_distilled_kaitlineryan99","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_sst2_distilled_kaitlineryan99| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/kaitlineryan99/tiny-bert-sst2-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_sst2_distilled_kushaljoseph_en.md b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_sst2_distilled_kushaljoseph_en.md new file mode 100644 index 00000000000000..720694324591fb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_sst2_distilled_kushaljoseph_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tiny_bert_sst2_distilled_kushaljoseph BertForSequenceClassification from kushaljoseph +author: John Snow Labs +name: tiny_bert_sst2_distilled_kushaljoseph +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_sst2_distilled_kushaljoseph` is a English model originally trained by kushaljoseph. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_sst2_distilled_kushaljoseph_en_5.1.4_3.4_1698234651704.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_sst2_distilled_kushaljoseph_en_5.1.4_3.4_1698234651704.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_sst2_distilled_kushaljoseph","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_sst2_distilled_kushaljoseph","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_sst2_distilled_kushaljoseph| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/kushaljoseph/tiny-bert-sst2-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_sst2_distilled_l4_h_512_new_en.md b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_sst2_distilled_l4_h_512_new_en.md new file mode 100644 index 00000000000000..fa7d7f8643fce7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_sst2_distilled_l4_h_512_new_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tiny_bert_sst2_distilled_l4_h_512_new BertForSequenceClassification from Smith123 +author: John Snow Labs +name: tiny_bert_sst2_distilled_l4_h_512_new +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_sst2_distilled_l4_h_512_new` is a English model originally trained by Smith123. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_sst2_distilled_l4_h_512_new_en_5.1.4_3.4_1698265791333.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_sst2_distilled_l4_h_512_new_en_5.1.4_3.4_1698265791333.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_sst2_distilled_l4_h_512_new","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_sst2_distilled_l4_h_512_new","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_sst2_distilled_l4_h_512_new| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|197.3 MB| + +## References + +https://huggingface.co/Smith123/tiny-bert-sst2-distilled_L4_H_512_New \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_sst2_distilled_sayan01_en.md b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_sst2_distilled_sayan01_en.md new file mode 100644 index 00000000000000..8f6291197995f2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_sst2_distilled_sayan01_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tiny_bert_sst2_distilled_sayan01 BertForSequenceClassification from Sayan01 +author: John Snow Labs +name: tiny_bert_sst2_distilled_sayan01 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_sst2_distilled_sayan01` is a English model originally trained by Sayan01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_sst2_distilled_sayan01_en_5.1.4_3.4_1698192322663.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_sst2_distilled_sayan01_en_5.1.4_3.4_1698192322663.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_sst2_distilled_sayan01","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_sst2_distilled_sayan01","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_sst2_distilled_sayan01| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|54.2 MB| + +## References + +https://huggingface.co/Sayan01/tiny-bert-sst2-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_sst2_distilled_smith123_en.md b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_sst2_distilled_smith123_en.md new file mode 100644 index 00000000000000..63e50b39464580 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_sst2_distilled_smith123_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tiny_bert_sst2_distilled_smith123 BertForSequenceClassification from Smith123 +author: John Snow Labs +name: tiny_bert_sst2_distilled_smith123 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_sst2_distilled_smith123` is a English model originally trained by Smith123. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_sst2_distilled_smith123_en_5.1.4_3.4_1698210672627.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_sst2_distilled_smith123_en_5.1.4_3.4_1698210672627.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_sst2_distilled_smith123","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_sst2_distilled_smith123","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_sst2_distilled_smith123| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|42.1 MB| + +## References + +https://huggingface.co/Smith123/tiny-bert-sst2-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_sst2_distilled_youssef320_en.md b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_sst2_distilled_youssef320_en.md new file mode 100644 index 00000000000000..0ecb380b17dfe7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_sst2_distilled_youssef320_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tiny_bert_sst2_distilled_youssef320 BertForSequenceClassification from Youssef320 +author: John Snow Labs +name: tiny_bert_sst2_distilled_youssef320 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_sst2_distilled_youssef320` is a English model originally trained by Youssef320. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_sst2_distilled_youssef320_en_5.1.4_3.4_1698212716468.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_sst2_distilled_youssef320_en_5.1.4_3.4_1698212716468.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_sst2_distilled_youssef320","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_sst2_distilled_youssef320","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_sst2_distilled_youssef320| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/Youssef320/tiny-bert-sst2-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_stsb_distilled_en.md b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_stsb_distilled_en.md new file mode 100644 index 00000000000000..460dc400beeca7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_stsb_distilled_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tiny_bert_stsb_distilled BertForSequenceClassification from Sayan01 +author: John Snow Labs +name: tiny_bert_stsb_distilled +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_stsb_distilled` is a English model originally trained by Sayan01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_stsb_distilled_en_5.1.4_3.4_1698269125608.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_stsb_distilled_en_5.1.4_3.4_1698269125608.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_stsb_distilled","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_stsb_distilled","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_stsb_distilled| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|54.2 MB| + +## References + +https://huggingface.co/Sayan01/tiny-bert-stsb-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_wnli_distilled_en.md b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_wnli_distilled_en.md new file mode 100644 index 00000000000000..46549eb6781535 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tiny_bert_wnli_distilled_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tiny_bert_wnli_distilled BertForSequenceClassification from Sayan01 +author: John Snow Labs +name: tiny_bert_wnli_distilled +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_wnli_distilled` is a English model originally trained by Sayan01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_wnli_distilled_en_5.1.4_3.4_1698211599601.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_wnli_distilled_en_5.1.4_3.4_1698211599601.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_wnli_distilled","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_wnli_distilled","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_wnli_distilled| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|54.2 MB| + +## References + +https://huggingface.co/Sayan01/tiny-bert-wnli-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tonely_bert_en.md b/docs/_posts/ahmedlone127/2023-10-25-tonely_bert_en.md new file mode 100644 index 00000000000000..d28bb22dad1362 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tonely_bert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tonely_bert BertForSequenceClassification from francheska-vicente +author: John Snow Labs +name: tonely_bert +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tonely_bert` is a English model originally trained by francheska-vicente. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tonely_bert_en_5.1.4_3.4_1698223349625.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tonely_bert_en_5.1.4_3.4_1698223349625.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tonely_bert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tonely_bert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tonely_bert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|406.0 MB| + +## References + +https://huggingface.co/francheska-vicente/tonely-bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tweet_bert_1408_en.md b/docs/_posts/ahmedlone127/2023-10-25-tweet_bert_1408_en.md new file mode 100644 index 00000000000000..c81973e035dab2 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tweet_bert_1408_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tweet_bert_1408 BertForSequenceClassification from dsmsb +author: John Snow Labs +name: tweet_bert_1408 +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tweet_bert_1408` is a English model originally trained by dsmsb. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tweet_bert_1408_en_5.1.4_3.4_1698266582244.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tweet_bert_1408_en_5.1.4_3.4_1698266582244.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tweet_bert_1408","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tweet_bert_1408","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tweet_bert_1408| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|667.3 MB| + +## References + +https://huggingface.co/dsmsb/tweet_bert_1408 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tweet_sentiments_analysis_bert_jedida_en.md b/docs/_posts/ahmedlone127/2023-10-25-tweet_sentiments_analysis_bert_jedida_en.md new file mode 100644 index 00000000000000..dd97e9eeef963b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tweet_sentiments_analysis_bert_jedida_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tweet_sentiments_analysis_bert_jedida BertForSequenceClassification from Jedida +author: John Snow Labs +name: tweet_sentiments_analysis_bert_jedida +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tweet_sentiments_analysis_bert_jedida` is a English model originally trained by Jedida. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tweet_sentiments_analysis_bert_jedida_en_5.1.4_3.4_1698199772330.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tweet_sentiments_analysis_bert_jedida_en_5.1.4_3.4_1698199772330.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tweet_sentiments_analysis_bert_jedida","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tweet_sentiments_analysis_bert_jedida","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tweet_sentiments_analysis_bert_jedida| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Jedida/tweet_sentiments_analysis_bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tweet_sentiments_analysis_bert_kingasiedu_en.md b/docs/_posts/ahmedlone127/2023-10-25-tweet_sentiments_analysis_bert_kingasiedu_en.md new file mode 100644 index 00000000000000..04b4ce374eba38 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tweet_sentiments_analysis_bert_kingasiedu_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tweet_sentiments_analysis_bert_kingasiedu BertForSequenceClassification from KingAsiedu +author: John Snow Labs +name: tweet_sentiments_analysis_bert_kingasiedu +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tweet_sentiments_analysis_bert_kingasiedu` is a English model originally trained by KingAsiedu. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tweet_sentiments_analysis_bert_kingasiedu_en_5.1.4_3.4_1698198506026.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tweet_sentiments_analysis_bert_kingasiedu_en_5.1.4_3.4_1698198506026.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tweet_sentiments_analysis_bert_kingasiedu","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tweet_sentiments_analysis_bert_kingasiedu","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tweet_sentiments_analysis_bert_kingasiedu| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/KingAsiedu/tweet_sentiments_analysis_bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tweet_sentiments_analysis_bert_penscola_en.md b/docs/_posts/ahmedlone127/2023-10-25-tweet_sentiments_analysis_bert_penscola_en.md new file mode 100644 index 00000000000000..ed126b9689a5cb --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tweet_sentiments_analysis_bert_penscola_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tweet_sentiments_analysis_bert_penscola BertForSequenceClassification from penscola +author: John Snow Labs +name: tweet_sentiments_analysis_bert_penscola +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tweet_sentiments_analysis_bert_penscola` is a English model originally trained by penscola. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tweet_sentiments_analysis_bert_penscola_en_5.1.4_3.4_1698197498186.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tweet_sentiments_analysis_bert_penscola_en_5.1.4_3.4_1698197498186.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tweet_sentiments_analysis_bert_penscola","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tweet_sentiments_analysis_bert_penscola","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tweet_sentiments_analysis_bert_penscola| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/penscola/tweet_sentiments_analysis_bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tweet_sentiments_analysis_bert_uholodala_en.md b/docs/_posts/ahmedlone127/2023-10-25-tweet_sentiments_analysis_bert_uholodala_en.md new file mode 100644 index 00000000000000..b0dc567b573372 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tweet_sentiments_analysis_bert_uholodala_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tweet_sentiments_analysis_bert_uholodala BertForSequenceClassification from UholoDala +author: John Snow Labs +name: tweet_sentiments_analysis_bert_uholodala +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tweet_sentiments_analysis_bert_uholodala` is a English model originally trained by UholoDala. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tweet_sentiments_analysis_bert_uholodala_en_5.1.4_3.4_1698193855869.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tweet_sentiments_analysis_bert_uholodala_en_5.1.4_3.4_1698193855869.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tweet_sentiments_analysis_bert_uholodala","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tweet_sentiments_analysis_bert_uholodala","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tweet_sentiments_analysis_bert_uholodala| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/UholoDala/tweet_sentiments_analysis_bert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-twitter_disaster_bert_large_en.md b/docs/_posts/ahmedlone127/2023-10-25-twitter_disaster_bert_large_en.md new file mode 100644 index 00000000000000..54e97698c2eb2c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-twitter_disaster_bert_large_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English twitter_disaster_bert_large BertForSequenceClassification from ReynaQuita +author: John Snow Labs +name: twitter_disaster_bert_large +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`twitter_disaster_bert_large` is a English model originally trained by ReynaQuita. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/twitter_disaster_bert_large_en_5.1.4_3.4_1698238716080.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/twitter_disaster_bert_large_en_5.1.4_3.4_1698238716080.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("twitter_disaster_bert_large","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("twitter_disaster_bert_large","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|twitter_disaster_bert_large| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/ReynaQuita/twitter_disaster_bert_large \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-tyson_bert_base_cased_en.md b/docs/_posts/ahmedlone127/2023-10-25-tyson_bert_base_cased_en.md new file mode 100644 index 00000000000000..564654d2570295 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-tyson_bert_base_cased_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tyson_bert_base_cased BertForSequenceClassification from tyson0420 +author: John Snow Labs +name: tyson_bert_base_cased +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tyson_bert_base_cased` is a English model originally trained by tyson0420. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tyson_bert_base_cased_en_5.1.4_3.4_1698265052918.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tyson_bert_base_cased_en_5.1.4_3.4_1698265052918.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tyson_bert_base_cased","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tyson_bert_base_cased","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tyson_bert_base_cased| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/tyson0420/tyson-bert-base-cased \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-vashkontrol_sentiment_rubert_ru.md b/docs/_posts/ahmedlone127/2023-10-25-vashkontrol_sentiment_rubert_ru.md new file mode 100644 index 00000000000000..2c70fdca761862 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-vashkontrol_sentiment_rubert_ru.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Russian vashkontrol_sentiment_rubert BertForSequenceClassification from kartashoffv +author: John Snow Labs +name: vashkontrol_sentiment_rubert +date: 2023-10-25 +tags: [bert, ru, open_source, sequence_classification, onnx] +task: Text Classification +language: ru +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`vashkontrol_sentiment_rubert` is a Russian model originally trained by kartashoffv. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/vashkontrol_sentiment_rubert_ru_5.1.4_3.4_1698206312526.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/vashkontrol_sentiment_rubert_ru_5.1.4_3.4_1698206312526.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("vashkontrol_sentiment_rubert","ru")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("vashkontrol_sentiment_rubert","ru") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|vashkontrol_sentiment_rubert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|ru| +|Size:|666.5 MB| + +## References + +https://huggingface.co/kartashoffv/vashkontrol-sentiment-rubert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-xlm_bert_go_emotions_en.md b/docs/_posts/ahmedlone127/2023-10-25-xlm_bert_go_emotions_en.md new file mode 100644 index 00000000000000..3a3add25fea6f1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-xlm_bert_go_emotions_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English xlm_bert_go_emotions BertForSequenceClassification from SchuylerH +author: John Snow Labs +name: xlm_bert_go_emotions +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`xlm_bert_go_emotions` is a English model originally trained by SchuylerH. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/xlm_bert_go_emotions_en_5.1.4_3.4_1698204430255.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/xlm_bert_go_emotions_en_5.1.4_3.4_1698204430255.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("xlm_bert_go_emotions","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("xlm_bert_go_emotions","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|xlm_bert_go_emotions| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|667.3 MB| + +## References + +https://huggingface.co/SchuylerH/xlm-bert-go-emotions \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-ziwei_bert_imdb_en.md b/docs/_posts/ahmedlone127/2023-10-25-ziwei_bert_imdb_en.md new file mode 100644 index 00000000000000..67179ddbed43e5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-ziwei_bert_imdb_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English ziwei_bert_imdb BertForSequenceClassification from ZiweiG +author: John Snow Labs +name: ziwei_bert_imdb +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ziwei_bert_imdb` is a English model originally trained by ZiweiG. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ziwei_bert_imdb_en_5.1.4_3.4_1698269066935.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ziwei_bert_imdb_en_5.1.4_3.4_1698269066935.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("ziwei_bert_imdb","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("ziwei_bert_imdb","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ziwei_bert_imdb| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/ZiweiG/ziwei-bert-imdb \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-25-ziwei_bertimdb_prob_en.md b/docs/_posts/ahmedlone127/2023-10-25-ziwei_bertimdb_prob_en.md new file mode 100644 index 00000000000000..b3f573a54107c0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-25-ziwei_bertimdb_prob_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English ziwei_bertimdb_prob BertForSequenceClassification from ZiweiG +author: John Snow Labs +name: ziwei_bertimdb_prob +date: 2023-10-25 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`ziwei_bertimdb_prob` is a English model originally trained by ZiweiG. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/ziwei_bertimdb_prob_en_5.1.4_3.4_1698269802501.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/ziwei_bertimdb_prob_en_5.1.4_3.4_1698269802501.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("ziwei_bertimdb_prob","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("ziwei_bertimdb_prob","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|ziwei_bertimdb_prob| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/ZiweiG/ziwei-bertimdb-prob \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_31_en.md b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_31_en.md new file mode 100644 index 00000000000000..be459d228640c9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_31_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_31 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_31 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_31` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_31_en_5.1.4_3.4_1698279222298.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_31_en_5.1.4_3.4_1698279222298.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_31","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_31","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_31| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-31 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_32_en.md b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_32_en.md new file mode 100644 index 00000000000000..28ca593f6fc85c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_32_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_32 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_32 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_32` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_32_en_5.1.4_3.4_1698280115141.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_32_en_5.1.4_3.4_1698280115141.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_32","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_32","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_32| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-32 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_33_en.md b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_33_en.md new file mode 100644 index 00000000000000..d4852066bf9432 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_33_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_33 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_33 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_33` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_33_en_5.1.4_3.4_1698280969297.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_33_en_5.1.4_3.4_1698280969297.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_33","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_33","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_33| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-33 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_34_en.md b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_34_en.md new file mode 100644 index 00000000000000..4f5650c1de1ff7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_34_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_34 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_34 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_34` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_34_en_5.1.4_3.4_1698281806567.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_34_en_5.1.4_3.4_1698281806567.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_34","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_34","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_34| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-34 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_35_en.md b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_35_en.md new file mode 100644 index 00000000000000..9279975d9e2b40 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_35_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_35 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_35 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_35` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_35_en_5.1.4_3.4_1698282610041.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_35_en_5.1.4_3.4_1698282610041.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_35","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_35","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_35| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-35 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_36_en.md b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_36_en.md new file mode 100644 index 00000000000000..63e966ea315dd6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_36_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_36 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_36 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_36` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_36_en_5.1.4_3.4_1698283422017.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_36_en_5.1.4_3.4_1698283422017.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_36","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_36","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_36| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-36 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_37_en.md b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_37_en.md new file mode 100644 index 00000000000000..336e55ac3050a6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_37_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_37 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_37 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_37` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_37_en_5.1.4_3.4_1698284352951.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_37_en_5.1.4_3.4_1698284352951.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_37","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_37","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_37| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-37 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_38_en.md b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_38_en.md new file mode 100644 index 00000000000000..0efa5d1dbe9a86 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_38_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_38 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_38 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_38` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_38_en_5.1.4_3.4_1698285115826.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_38_en_5.1.4_3.4_1698285115826.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_38","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_38","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_38| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-38 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_39_en.md b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_39_en.md new file mode 100644 index 00000000000000..23d04e5dfc9af5 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_39_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_39 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_39 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_39` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_39_en_5.1.4_3.4_1698286112629.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_39_en_5.1.4_3.4_1698286112629.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_39","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_39","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_39| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-39 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_40_en.md b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_40_en.md new file mode 100644 index 00000000000000..3426f7c18c47d4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_40_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_40 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_40 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_40` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_40_en_5.1.4_3.4_1698287281956.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_40_en_5.1.4_3.4_1698287281956.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_40","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_40","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_40| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-40 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_41_en.md b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_41_en.md new file mode 100644 index 00000000000000..93d42590296b2d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_41_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_41 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_41 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_41` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_41_en_5.1.4_3.4_1698288102738.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_41_en_5.1.4_3.4_1698288102738.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_41","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_41","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_41| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-41 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_42_en.md b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_42_en.md new file mode 100644 index 00000000000000..7fe1a22bb1ba44 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_42_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_42 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_42 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_42` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_42_en_5.1.4_3.4_1698288911852.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_42_en_5.1.4_3.4_1698288911852.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_42","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_42","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_42| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-42 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_43_en.md b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_43_en.md new file mode 100644 index 00000000000000..63508b531c145e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_43_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_43 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_43 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_43` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_43_en_5.1.4_3.4_1698289802693.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_43_en_5.1.4_3.4_1698289802693.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_43","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_43","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_43| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-43 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_44_en.md b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_44_en.md new file mode 100644 index 00000000000000..be5bf80e190d33 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_44_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_44 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_44 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_44` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_44_en_5.1.4_3.4_1698290656405.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_44_en_5.1.4_3.4_1698290656405.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_44","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_44","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_44| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-44 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_45_en.md b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_45_en.md new file mode 100644 index 00000000000000..0b3f9bf1fbb430 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_45_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_45 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_45 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_45` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_45_en_5.1.4_3.4_1698291394442.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_45_en_5.1.4_3.4_1698291394442.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_45","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_45","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_45| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-45 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_46_en.md b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_46_en.md new file mode 100644 index 00000000000000..25884f90e3c889 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_46_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_46 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_46 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_46` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_46_en_5.1.4_3.4_1698292222009.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_46_en_5.1.4_3.4_1698292222009.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_46","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_46","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_46| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-46 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_47_en.md b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_47_en.md new file mode 100644 index 00000000000000..486e7412dfba3e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_47_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_47 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_47 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_47` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_47_en_5.1.4_3.4_1698292980207.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_47_en_5.1.4_3.4_1698292980207.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_47","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_47","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_47| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-47 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_48_en.md b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_48_en.md new file mode 100644 index 00000000000000..2ff46a75a01552 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-6ep_bert_ft_cola_48_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English 6ep_bert_ft_cola_48 BertForSequenceClassification from Jeevesh8 +author: John Snow Labs +name: 6ep_bert_ft_cola_48 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`6ep_bert_ft_cola_48` is a English model originally trained by Jeevesh8. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_48_en_5.1.4_3.4_1698294005792.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/6ep_bert_ft_cola_48_en_5.1.4_3.4_1698294005792.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_48","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("6ep_bert_ft_cola_48","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|6ep_bert_ft_cola_48| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Jeevesh8/6ep_bert_ft_cola-48 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-autonlp_alberti_stanza_names_34318169_en.md b/docs/_posts/ahmedlone127/2023-10-26-autonlp_alberti_stanza_names_34318169_en.md new file mode 100644 index 00000000000000..7d432149903c0b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-autonlp_alberti_stanza_names_34318169_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English autonlp_alberti_stanza_names_34318169 BertForSequenceClassification from alvp +author: John Snow Labs +name: autonlp_alberti_stanza_names_34318169 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`autonlp_alberti_stanza_names_34318169` is a English model originally trained by alvp. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/autonlp_alberti_stanza_names_34318169_en_5.1.4_3.4_1698284856096.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/autonlp_alberti_stanza_names_34318169_en_5.1.4_3.4_1698284856096.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("autonlp_alberti_stanza_names_34318169","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("autonlp_alberti_stanza_names_34318169","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|autonlp_alberti_stanza_names_34318169| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|666.7 MB| + +## References + +https://huggingface.co/alvp/autonlp-alberti-stanza-names-34318169 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_base_emotion_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_base_emotion_en.md new file mode 100644 index 00000000000000..6cf358f69ff907 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_base_emotion_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_emotion BertForSequenceClassification from Anonymous1111 +author: John Snow Labs +name: bert_base_emotion +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_emotion` is a English model originally trained by Anonymous1111. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_emotion_en_5.1.4_3.4_1698294005799.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_emotion_en_5.1.4_3.4_1698294005799.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_emotion","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_emotion","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_emotion| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Anonymous1111/bert-base-emotion \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_base_mnli_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_base_mnli_en.md new file mode 100644 index 00000000000000..b4ca0925e215cf --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_base_mnli_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_mnli BertForSequenceClassification from aloxatel +author: John Snow Labs +name: bert_base_mnli +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_mnli` is a English model originally trained by aloxatel. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_mnli_en_5.1.4_3.4_1698283550584.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_mnli_en_5.1.4_3.4_1698283550584.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_mnli","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_mnli","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_mnli| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/aloxatel/bert-base-mnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_base_nli_mean_tokens_finetuned_polifact_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_base_nli_mean_tokens_finetuned_polifact_en.md new file mode 100644 index 00000000000000..1236e442092002 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_base_nli_mean_tokens_finetuned_polifact_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_nli_mean_tokens_finetuned_polifact BertForSequenceClassification from anuj55 +author: John Snow Labs +name: bert_base_nli_mean_tokens_finetuned_polifact +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_nli_mean_tokens_finetuned_polifact` is a English model originally trained by anuj55. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_nli_mean_tokens_finetuned_polifact_en_5.1.4_3.4_1698279222275.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_nli_mean_tokens_finetuned_polifact_en_5.1.4_3.4_1698279222275.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_nli_mean_tokens_finetuned_polifact","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_nli_mean_tokens_finetuned_polifact","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_nli_mean_tokens_finetuned_polifact| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/anuj55/bert-base-nli-mean-tokens-finetuned-polifact \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_fine_tune_winogrande_ep_8_original_2e_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_fine_tune_winogrande_ep_8_original_2e_en.md new file mode 100644 index 00000000000000..0c4ac9749d6c77 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_fine_tune_winogrande_ep_8_original_2e_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_fine_tune_winogrande_ep_8_original_2e BertForSequenceClassification from Stupendousabhi +author: John Snow Labs +name: bert_base_uncased_fine_tune_winogrande_ep_8_original_2e +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_fine_tune_winogrande_ep_8_original_2e` is a English model originally trained by Stupendousabhi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_fine_tune_winogrande_ep_8_original_2e_en_5.1.4_3.4_1698291041785.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_fine_tune_winogrande_ep_8_original_2e_en_5.1.4_3.4_1698291041785.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_fine_tune_winogrande_ep_8_original_2e","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_fine_tune_winogrande_ep_8_original_2e","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_fine_tune_winogrande_ep_8_original_2e| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Stupendousabhi/bert-base-uncased-fine-tune-winogrande-ep-8_original-2e \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_addresso_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_addresso_en.md new file mode 100644 index 00000000000000..18531b679e74b6 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_addresso_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_addresso BertForSequenceClassification from annafavaro +author: John Snow Labs +name: bert_base_uncased_finetuned_addresso +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_addresso` is a English model originally trained by annafavaro. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_addresso_en_5.1.4_3.4_1698291251858.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_addresso_en_5.1.4_3.4_1698291251858.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_addresso","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_addresso","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_addresso| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/annafavaro/bert-base-uncased-finetuned-addresso \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_coda19_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_coda19_en.md new file mode 100644 index 00000000000000..ecc5a08e47e861 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_coda19_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_coda19 BertForSequenceClassification from appleternity +author: John Snow Labs +name: bert_base_uncased_finetuned_coda19 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_coda19` is a English model originally trained by appleternity. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_coda19_en_5.1.4_3.4_1698292061198.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_coda19_en_5.1.4_3.4_1698292061198.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_coda19","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_coda19","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_coda19| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/appleternity/bert-base-uncased-finetuned-coda19 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_cola_anirudh21_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_cola_anirudh21_en.md new file mode 100644 index 00000000000000..0b53da7de7c37d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_cola_anirudh21_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_cola_anirudh21 BertForSequenceClassification from anirudh21 +author: John Snow Labs +name: bert_base_uncased_finetuned_cola_anirudh21 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_cola_anirudh21` is a English model originally trained by anirudh21. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_anirudh21_en_5.1.4_3.4_1698287133978.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_cola_anirudh21_en_5.1.4_3.4_1698287133978.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_anirudh21","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_cola_anirudh21","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_cola_anirudh21| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/anirudh21/bert-base-uncased-finetuned-cola \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_mrpc_ajrae_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_mrpc_ajrae_en.md new file mode 100644 index 00000000000000..4cd85698bfb711 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_mrpc_ajrae_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_mrpc_ajrae BertForSequenceClassification from ajrae +author: John Snow Labs +name: bert_base_uncased_finetuned_mrpc_ajrae +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_mrpc_ajrae` is a English model originally trained by ajrae. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mrpc_ajrae_en_5.1.4_3.4_1698279222304.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mrpc_ajrae_en_5.1.4_3.4_1698279222304.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_mrpc_ajrae","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_mrpc_ajrae","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_mrpc_ajrae| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ajrae/bert-base-uncased-finetuned-mrpc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_mrpc_anirudh21_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_mrpc_anirudh21_en.md new file mode 100644 index 00000000000000..c0489e63661ca9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_mrpc_anirudh21_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_mrpc_anirudh21 BertForSequenceClassification from anirudh21 +author: John Snow Labs +name: bert_base_uncased_finetuned_mrpc_anirudh21 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_mrpc_anirudh21` is a English model originally trained by anirudh21. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mrpc_anirudh21_en_5.1.4_3.4_1698288102806.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_mrpc_anirudh21_en_5.1.4_3.4_1698288102806.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_mrpc_anirudh21","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_mrpc_anirudh21","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_mrpc_anirudh21| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/anirudh21/bert-base-uncased-finetuned-mrpc \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_qnli_anirudh21_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_qnli_anirudh21_en.md new file mode 100644 index 00000000000000..58aeab0b022353 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_qnli_anirudh21_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_qnli_anirudh21 BertForSequenceClassification from anirudh21 +author: John Snow Labs +name: bert_base_uncased_finetuned_qnli_anirudh21 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_qnli_anirudh21` is a English model originally trained by anirudh21. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_qnli_anirudh21_en_5.1.4_3.4_1698288910566.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_qnli_anirudh21_en_5.1.4_3.4_1698288910566.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_qnli_anirudh21","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_qnli_anirudh21","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_qnli_anirudh21| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/anirudh21/bert-base-uncased-finetuned-qnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_rte_anirudh21_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_rte_anirudh21_en.md new file mode 100644 index 00000000000000..897e06481cb5fd --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_rte_anirudh21_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_rte_anirudh21 BertForSequenceClassification from anirudh21 +author: John Snow Labs +name: bert_base_uncased_finetuned_rte_anirudh21 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_rte_anirudh21` is a English model originally trained by anirudh21. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_rte_anirudh21_en_5.1.4_3.4_1698289621082.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_rte_anirudh21_en_5.1.4_3.4_1698289621082.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_rte_anirudh21","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_rte_anirudh21","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_rte_anirudh21| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/anirudh21/bert-base-uncased-finetuned-rte \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_wnli_anirudh21_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_wnli_anirudh21_en.md new file mode 100644 index 00000000000000..d4309b42d6fdff --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_finetuned_wnli_anirudh21_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_finetuned_wnli_anirudh21 BertForSequenceClassification from anirudh21 +author: John Snow Labs +name: bert_base_uncased_finetuned_wnli_anirudh21 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_finetuned_wnli_anirudh21` is a English model originally trained by anirudh21. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_wnli_anirudh21_en_5.1.4_3.4_1698290332780.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_finetuned_wnli_anirudh21_en_5.1.4_3.4_1698290332780.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_wnli_anirudh21","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_finetuned_wnli_anirudh21","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_finetuned_wnli_anirudh21| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/anirudh21/bert-base-uncased-finetuned-wnli \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_itr0_0_0001_all_01_03_2022_14_08_15_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_itr0_0_0001_all_01_03_2022_14_08_15_en.md new file mode 100644 index 00000000000000..bdc208ff24728d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_itr0_0_0001_all_01_03_2022_14_08_15_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_itr0_0_0001_all_01_03_2022_14_08_15 BertForSequenceClassification from ali2066 +author: John Snow Labs +name: bert_base_uncased_itr0_0_0001_all_01_03_2022_14_08_15 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_itr0_0_0001_all_01_03_2022_14_08_15` is a English model originally trained by ali2066. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_itr0_0_0001_all_01_03_2022_14_08_15_en_5.1.4_3.4_1698281981852.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_itr0_0_0001_all_01_03_2022_14_08_15_en_5.1.4_3.4_1698281981852.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_itr0_0_0001_all_01_03_2022_14_08_15","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_itr0_0_0001_all_01_03_2022_14_08_15","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_itr0_0_0001_all_01_03_2022_14_08_15| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ali2066/bert_base_uncased_itr0_0.0001_all_01_03_2022-14_08_15 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_itr0_0_0001_webdiscourse_01_03_2022_16_08_12_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_itr0_0_0001_webdiscourse_01_03_2022_16_08_12_en.md new file mode 100644 index 00000000000000..06987010647a48 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_base_uncased_itr0_0_0001_webdiscourse_01_03_2022_16_08_12_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_base_uncased_itr0_0_0001_webdiscourse_01_03_2022_16_08_12 BertForSequenceClassification from ali2066 +author: John Snow Labs +name: bert_base_uncased_itr0_0_0001_webdiscourse_01_03_2022_16_08_12 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_base_uncased_itr0_0_0001_webdiscourse_01_03_2022_16_08_12` is a English model originally trained by ali2066. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_base_uncased_itr0_0_0001_webdiscourse_01_03_2022_16_08_12_en_5.1.4_3.4_1698282705485.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_base_uncased_itr0_0_0001_webdiscourse_01_03_2022_16_08_12_en_5.1.4_3.4_1698282705485.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_itr0_0_0001_webdiscourse_01_03_2022_16_08_12","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_base_uncased_itr0_0_0001_webdiscourse_01_03_2022_16_08_12","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_base_uncased_itr0_0_0001_webdiscourse_01_03_2022_16_08_12| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/ali2066/bert_base_uncased_itr0_0.0001_webDiscourse_01_03_2022-16_08_12 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_classifier_2e16_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_classifier_2e16_en.md new file mode 100644 index 00000000000000..927b5475aaeaca --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_classifier_2e16_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_classifier_2e16 BertForSequenceClassification from arthurbittencourt +author: John Snow Labs +name: bert_classifier_2e16 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_2e16` is a English model originally trained by arthurbittencourt. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_2e16_en_5.1.4_3.4_1698283785614.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_2e16_en_5.1.4_3.4_1698283785614.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_classifier_2e16","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_classifier_2e16","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_2e16| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/arthurbittencourt/bert_classifier_2e16 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_classifier_base_cased_chuvash_studio_name_medium_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_classifier_base_cased_chuvash_studio_name_medium_en.md new file mode 100644 index 00000000000000..37212fed67eaa4 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_classifier_base_cased_chuvash_studio_name_medium_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_classifier_base_cased_chuvash_studio_name_medium BertForSequenceClassification from jhonparra18 +author: John Snow Labs +name: bert_classifier_base_cased_chuvash_studio_name_medium +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_classifier_base_cased_chuvash_studio_name_medium` is a English model originally trained by jhonparra18. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_classifier_base_cased_chuvash_studio_name_medium_en_5.1.4_3.4_1698289061093.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_classifier_base_cased_chuvash_studio_name_medium_en_5.1.4_3.4_1698289061093.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_classifier_base_cased_chuvash_studio_name_medium","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_classifier_base_cased_chuvash_studio_name_medium","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_classifier_base_cased_chuvash_studio_name_medium| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/jhonparra18/bert-base-cased-cv-studio_name-medium \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_eatable_classification_english_russian_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_eatable_classification_english_russian_en.md new file mode 100644 index 00000000000000..53033e8fceb4b1 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_eatable_classification_english_russian_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_eatable_classification_english_russian BertForSequenceClassification from alexander-karpov +author: John Snow Labs +name: bert_eatable_classification_english_russian +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_eatable_classification_english_russian` is a English model originally trained by alexander-karpov. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_eatable_classification_english_russian_en_5.1.4_3.4_1698281067230.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_eatable_classification_english_russian_en_5.1.4_3.4_1698281067230.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_eatable_classification_english_russian","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_eatable_classification_english_russian","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_eatable_classification_english_russian| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|482.5 MB| + +## References + +https://huggingface.co/alexander-karpov/bert-eatable-classification-en-ru \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_finetuned_char_classification_e81_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_finetuned_char_classification_e81_en.md new file mode 100644 index 00000000000000..2774fad129c405 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_finetuned_char_classification_e81_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_finetuned_char_classification_e81 BertForSequenceClassification from bhagasra-saurav +author: John Snow Labs +name: bert_finetuned_char_classification_e81 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_char_classification_e81` is a English model originally trained by bhagasra-saurav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_char_classification_e81_en_5.1.4_3.4_1698288809765.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_char_classification_e81_en_5.1.4_3.4_1698288809765.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_char_classification_e81","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_char_classification_e81","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_char_classification_e81| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/bhagasra-saurav/bert-finetuned-char-classification-e81 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_finetuned_char_classification_e8_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_finetuned_char_classification_e8_en.md new file mode 100644 index 00000000000000..8240fc7947993e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_finetuned_char_classification_e8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_finetuned_char_classification_e8 BertForSequenceClassification from bhagasra-saurav +author: John Snow Labs +name: bert_finetuned_char_classification_e8 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_finetuned_char_classification_e8` is a English model originally trained by bhagasra-saurav. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_finetuned_char_classification_e8_en_5.1.4_3.4_1698287074215.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_finetuned_char_classification_e8_en_5.1.4_3.4_1698287074215.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_char_classification_e8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_finetuned_char_classification_e8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_finetuned_char_classification_e8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/bhagasra-saurav/bert-finetuned-char-classification-e8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_large_uncased_fine_tune_winogrande_ep_8_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_large_uncased_fine_tune_winogrande_ep_8_en.md new file mode 100644 index 00000000000000..bd81daffaf725e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_large_uncased_fine_tune_winogrande_ep_8_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_fine_tune_winogrande_ep_8 BertForSequenceClassification from Stupendousabhi +author: John Snow Labs +name: bert_large_uncased_fine_tune_winogrande_ep_8 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_fine_tune_winogrande_ep_8` is a English model originally trained by Stupendousabhi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_fine_tune_winogrande_ep_8_en_5.1.4_3.4_1698286668181.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_fine_tune_winogrande_ep_8_en_5.1.4_3.4_1698286668181.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_fine_tune_winogrande_ep_8","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_fine_tune_winogrande_ep_8","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_fine_tune_winogrande_ep_8| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Stupendousabhi/bert-large-uncased-fine-tune-winogrande-ep-8 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_large_uncased_fine_tune_winogrande_ep_8_original_2e_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_large_uncased_fine_tune_winogrande_ep_8_original_2e_en.md new file mode 100644 index 00000000000000..91682889d17276 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_large_uncased_fine_tune_winogrande_ep_8_original_2e_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_fine_tune_winogrande_ep_8_original_2e BertForSequenceClassification from Stupendousabhi +author: John Snow Labs +name: bert_large_uncased_fine_tune_winogrande_ep_8_original_2e +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_fine_tune_winogrande_ep_8_original_2e` is a English model originally trained by Stupendousabhi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_fine_tune_winogrande_ep_8_original_2e_en_5.1.4_3.4_1698290167891.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_fine_tune_winogrande_ep_8_original_2e_en_5.1.4_3.4_1698290167891.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_fine_tune_winogrande_ep_8_original_2e","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_fine_tune_winogrande_ep_8_original_2e","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_fine_tune_winogrande_ep_8_original_2e| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Stupendousabhi/bert-large-uncased-fine-tune-winogrande-ep-8_original-2e \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_large_uncased_finetuned_winogrande_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_large_uncased_finetuned_winogrande_en.md new file mode 100644 index 00000000000000..b1ab6740671e16 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_large_uncased_finetuned_winogrande_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_finetuned_winogrande BertForSequenceClassification from Sumaia +author: John Snow Labs +name: bert_large_uncased_finetuned_winogrande +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_finetuned_winogrande` is a English model originally trained by Sumaia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_finetuned_winogrande_en_5.1.4_3.4_1698287902297.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_finetuned_winogrande_en_5.1.4_3.4_1698287902297.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_finetuned_winogrande","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_finetuned_winogrande","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_finetuned_winogrande| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/Sumaia/bert-large-uncased-finetuned-winogrande \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_large_uncased_hoax_classifier_fulltext_v1_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_large_uncased_hoax_classifier_fulltext_v1_en.md new file mode 100644 index 00000000000000..636d7838f2a225 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_large_uncased_hoax_classifier_fulltext_v1_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_large_uncased_hoax_classifier_fulltext_v1 BertForSequenceClassification from research-dump +author: John Snow Labs +name: bert_large_uncased_hoax_classifier_fulltext_v1 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_large_uncased_hoax_classifier_fulltext_v1` is a English model originally trained by research-dump. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_large_uncased_hoax_classifier_fulltext_v1_en_5.1.4_3.4_1698282011063.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_large_uncased_hoax_classifier_fulltext_v1_en_5.1.4_3.4_1698282011063.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_hoax_classifier_fulltext_v1","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_large_uncased_hoax_classifier_fulltext_v1","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_large_uncased_hoax_classifier_fulltext_v1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/research-dump/bert-large-uncased_hoax_classifier_fulltext_v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_multilingual_passage_reranking_msmarco_amberoad_xx.md b/docs/_posts/ahmedlone127/2023-10-26-bert_multilingual_passage_reranking_msmarco_amberoad_xx.md new file mode 100644 index 00000000000000..d0299054064397 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_multilingual_passage_reranking_msmarco_amberoad_xx.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Multilingual bert_multilingual_passage_reranking_msmarco_amberoad BertForSequenceClassification from amberoad +author: John Snow Labs +name: bert_multilingual_passage_reranking_msmarco_amberoad +date: 2023-10-26 +tags: [bert, xx, open_source, sequence_classification, onnx] +task: Text Classification +language: xx +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_multilingual_passage_reranking_msmarco_amberoad` is a Multilingual model originally trained by amberoad. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_multilingual_passage_reranking_msmarco_amberoad_xx_5.1.4_3.4_1698285856977.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_multilingual_passage_reranking_msmarco_amberoad_xx_5.1.4_3.4_1698285856977.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_multilingual_passage_reranking_msmarco_amberoad","xx")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_multilingual_passage_reranking_msmarco_amberoad","xx") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_multilingual_passage_reranking_msmarco_amberoad| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|xx| +|Size:|627.7 MB| + +## References + +https://huggingface.co/amberoad/bert-multilingual-passage-reranking-msmarco \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_turkish_text_classification_tr.md b/docs/_posts/ahmedlone127/2023-10-26-bert_turkish_text_classification_tr.md new file mode 100644 index 00000000000000..1e5ef266b3d323 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_turkish_text_classification_tr.md @@ -0,0 +1,97 @@ +--- +layout: model +title: Turkish bert_turkish_text_classification BertForSequenceClassification from akdeniz27 +author: John Snow Labs +name: bert_turkish_text_classification +date: 2023-10-26 +tags: [bert, tr, open_source, sequence_classification, onnx] +task: Text Classification +language: tr +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_turkish_text_classification` is a Turkish model originally trained by akdeniz27. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_turkish_text_classification_tr_5.1.4_3.4_1698280125422.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_turkish_text_classification_tr_5.1.4_3.4_1698280125422.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_turkish_text_classification","tr")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_turkish_text_classification","tr") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_turkish_text_classification| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|tr| +|Size:|414.5 MB| + +## References + +https://huggingface.co/akdeniz27/bert-turkish-text-classification \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_vast_binary_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_vast_binary_en.md new file mode 100644 index 00000000000000..818ab5ca89eed0 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_vast_binary_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_vast_binary BertForSequenceClassification from Babak-Behkamkia +author: John Snow Labs +name: bert_vast_binary +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_vast_binary` is a English model originally trained by Babak-Behkamkia. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_vast_binary_en_5.1.4_3.4_1698287964135.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_vast_binary_en_5.1.4_3.4_1698287964135.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_vast_binary","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_vast_binary","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_vast_binary| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/Babak-Behkamkia/bert_VAST_binary \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-bert_workforce_en.md b/docs/_posts/ahmedlone127/2023-10-26-bert_workforce_en.md new file mode 100644 index 00000000000000..371670d317776c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-bert_workforce_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English bert_workforce BertForSequenceClassification from cduesing +author: John Snow Labs +name: bert_workforce +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`bert_workforce` is a English model originally trained by cduesing. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_workforce_en_5.1.4_3.4_1698291042646.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_workforce_en_5.1.4_3.4_1698291042646.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("bert_workforce","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("bert_workforce","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|bert_workforce| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.6 MB| + +## References + +https://huggingface.co/cduesing/bert_workforce \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-dk_emotion_bert_in_class_ejaalborg2022_en.md b/docs/_posts/ahmedlone127/2023-10-26-dk_emotion_bert_in_class_ejaalborg2022_en.md new file mode 100644 index 00000000000000..47f669b144b055 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-dk_emotion_bert_in_class_ejaalborg2022_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English dk_emotion_bert_in_class_ejaalborg2022 BertForSequenceClassification from EJaalborg2022 +author: John Snow Labs +name: dk_emotion_bert_in_class_ejaalborg2022 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`dk_emotion_bert_in_class_ejaalborg2022` is a English model originally trained by EJaalborg2022. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/dk_emotion_bert_in_class_ejaalborg2022_en_5.1.4_3.4_1698281672475.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/dk_emotion_bert_in_class_ejaalborg2022_en_5.1.4_3.4_1698281672475.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("dk_emotion_bert_in_class_ejaalborg2022","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("dk_emotion_bert_in_class_ejaalborg2022","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|dk_emotion_bert_in_class_ejaalborg2022| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|414.6 MB| + +## References + +https://huggingface.co/EJaalborg2022/dk_emotion_bert_in_class \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-filbert_en.md b/docs/_posts/ahmedlone127/2023-10-26-filbert_en.md new file mode 100644 index 00000000000000..598a9d571a5101 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-filbert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English filbert BertForSequenceClassification from rajpurkarlab +author: John Snow Labs +name: filbert +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`filbert` is a English model originally trained by rajpurkarlab. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/filbert_en_5.1.4_3.4_1698292222031.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/filbert_en_5.1.4_3.4_1698292222031.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("filbert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("filbert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|filbert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|405.9 MB| + +## References + +https://huggingface.co/rajpurkarlab/filbert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-finbert_pb_en.md b/docs/_posts/ahmedlone127/2023-10-26-finbert_pb_en.md new file mode 100644 index 00000000000000..a1b34e78de3006 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-finbert_pb_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English finbert_pb BertForSequenceClassification from Forturne +author: John Snow Labs +name: finbert_pb +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finbert_pb` is a English model originally trained by Forturne. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finbert_pb_en_5.1.4_3.4_1698279849515.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finbert_pb_en_5.1.4_3.4_1698279849515.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("finbert_pb","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finbert_pb","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finbert_pb| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|411.6 MB| + +## References + +https://huggingface.co/Forturne/Finbert_PB \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-finbert_slow_en.md b/docs/_posts/ahmedlone127/2023-10-26-finbert_slow_en.md new file mode 100644 index 00000000000000..9aaa19e0aaeeac --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-finbert_slow_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English finbert_slow BertForSequenceClassification from Narsil +author: John Snow Labs +name: finbert_slow +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`finbert_slow` is a English model originally trained by Narsil. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/finbert_slow_en_5.1.4_3.4_1698288809467.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/finbert_slow_en_5.1.4_3.4_1698288809467.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("finbert_slow","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("finbert_slow","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|finbert_slow| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/Narsil/finbert-slow \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-fine_tune_mbert_combined_en.md b/docs/_posts/ahmedlone127/2023-10-26-fine_tune_mbert_combined_en.md new file mode 100644 index 00000000000000..09a52483c2ab2e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-fine_tune_mbert_combined_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English fine_tune_mbert_combined BertForSequenceClassification from nouman-10 +author: John Snow Labs +name: fine_tune_mbert_combined +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`fine_tune_mbert_combined` is a English model originally trained by nouman-10. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/fine_tune_mbert_combined_en_5.1.4_3.4_1698280869859.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/fine_tune_mbert_combined_en_5.1.4_3.4_1698280869859.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("fine_tune_mbert_combined","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("fine_tune_mbert_combined","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|fine_tune_mbert_combined| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|627.7 MB| + +## References + +https://huggingface.co/nouman-10/fine-tune-mbert-combined \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-kd_roberta_1lbert_lambda50_en.md b/docs/_posts/ahmedlone127/2023-10-26-kd_roberta_1lbert_lambda50_en.md new file mode 100644 index 00000000000000..53bd02f4cffb64 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-kd_roberta_1lbert_lambda50_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English kd_roberta_1lbert_lambda50 BertForSequenceClassification from Youssef320 +author: John Snow Labs +name: kd_roberta_1lbert_lambda50 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`kd_roberta_1lbert_lambda50` is a English model originally trained by Youssef320. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/kd_roberta_1lbert_lambda50_en_5.1.4_3.4_1698289193903.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/kd_roberta_1lbert_lambda50_en_5.1.4_3.4_1698289193903.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("kd_roberta_1lbert_lambda50","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("kd_roberta_1lbert_lambda50","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|kd_roberta_1lbert_lambda50| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|43.9 MB| + +## References + +https://huggingface.co/Youssef320/KD_Roberta_1LBERT_lambda50 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v1_en.md b/docs/_posts/ahmedlone127/2023-10-26-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v1_en.md new file mode 100644 index 00000000000000..c45fd4b7eddf16 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v1_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v1 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v1 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v1` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v1_en_5.1.4_3.4_1698291794941.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v1_en_5.1.4_3.4_1698291794941.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v1","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v1","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v1| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.1 MB| + +## References + +https://huggingface.co/hw2942/mengzi-bert-base-fin-wallstreetcn-morning-news-market-overview-SSEC-v1 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v2_en.md b/docs/_posts/ahmedlone127/2023-10-26-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v2_en.md new file mode 100644 index 00000000000000..d900164f5da98c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v2 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v2 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v2` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v2_en_5.1.4_3.4_1698292580801.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v2_en_5.1.4_3.4_1698292580801.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.1 MB| + +## References + +https://huggingface.co/hw2942/mengzi-bert-base-fin-wallstreetcn-morning-news-market-overview-SSEC-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v3_en.md b/docs/_posts/ahmedlone127/2023-10-26-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v3_en.md new file mode 100644 index 00000000000000..9ee9f01a503d7d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v3_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v3 BertForSequenceClassification from hw2942 +author: John Snow Labs +name: mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v3 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v3` is a English model originally trained by hw2942. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v3_en_5.1.4_3.4_1698293450177.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v3_en_5.1.4_3.4_1698293450177.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v3","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v3","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|mengzi_bert_base_fin_wallstreetcn_morning_news_market_overview_ssec_v3| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|383.1 MB| + +## References + +https://huggingface.co/hw2942/mengzi-bert-base-fin-wallstreetcn-morning-news-market-overview-SSEC-v3 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-model3_marabertv2_t1_wos_en.md b/docs/_posts/ahmedlone127/2023-10-26-model3_marabertv2_t1_wos_en.md new file mode 100644 index 00000000000000..3977ad58353fa9 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-model3_marabertv2_t1_wos_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English model3_marabertv2_t1_wos BertForSequenceClassification from Somah +author: John Snow Labs +name: model3_marabertv2_t1_wos +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model3_marabertv2_t1_wos` is a English model originally trained by Somah. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model3_marabertv2_t1_wos_en_5.1.4_3.4_1698278429002.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model3_marabertv2_t1_wos_en_5.1.4_3.4_1698278429002.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("model3_marabertv2_t1_wos","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("model3_marabertv2_t1_wos","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model3_marabertv2_t1_wos| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|608.8 MB| + +## References + +https://huggingface.co/Somah/Model3_Marabertv2_T1_WOS \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-model3_marabertv2_t1_ws_a100_en.md b/docs/_posts/ahmedlone127/2023-10-26-model3_marabertv2_t1_ws_a100_en.md new file mode 100644 index 00000000000000..cf7f086e5bb16b --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-model3_marabertv2_t1_ws_a100_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English model3_marabertv2_t1_ws_a100 BertForSequenceClassification from Somah +author: John Snow Labs +name: model3_marabertv2_t1_ws_a100 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model3_marabertv2_t1_ws_a100` is a English model originally trained by Somah. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model3_marabertv2_t1_ws_a100_en_5.1.4_3.4_1698283946931.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model3_marabertv2_t1_ws_a100_en_5.1.4_3.4_1698283946931.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("model3_marabertv2_t1_ws_a100","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("model3_marabertv2_t1_ws_a100","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model3_marabertv2_t1_ws_a100| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|608.8 MB| + +## References + +https://huggingface.co/Somah/Model3_Marabertv2_T1_WS_A100 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-model3_marabertv2_t2_wos_en.md b/docs/_posts/ahmedlone127/2023-10-26-model3_marabertv2_t2_wos_en.md new file mode 100644 index 00000000000000..88efa9d9128436 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-model3_marabertv2_t2_wos_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English model3_marabertv2_t2_wos BertForSequenceClassification from Somah +author: John Snow Labs +name: model3_marabertv2_t2_wos +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model3_marabertv2_t2_wos` is a English model originally trained by Somah. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model3_marabertv2_t2_wos_en_5.1.4_3.4_1698279331644.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model3_marabertv2_t2_wos_en_5.1.4_3.4_1698279331644.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("model3_marabertv2_t2_wos","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("model3_marabertv2_t2_wos","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model3_marabertv2_t2_wos| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|608.8 MB| + +## References + +https://huggingface.co/Somah/Model3_Marabertv2_T2_WOS \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-model3_marabertv2_t2_ws_a100_en.md b/docs/_posts/ahmedlone127/2023-10-26-model3_marabertv2_t2_ws_a100_en.md new file mode 100644 index 00000000000000..44cc3e1265abd7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-model3_marabertv2_t2_ws_a100_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English model3_marabertv2_t2_ws_a100 BertForSequenceClassification from Somah +author: John Snow Labs +name: model3_marabertv2_t2_ws_a100 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model3_marabertv2_t2_ws_a100` is a English model originally trained by Somah. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model3_marabertv2_t2_ws_a100_en_5.1.4_3.4_1698286112848.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model3_marabertv2_t2_ws_a100_en_5.1.4_3.4_1698286112848.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("model3_marabertv2_t2_ws_a100","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("model3_marabertv2_t2_ws_a100","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model3_marabertv2_t2_ws_a100| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|608.8 MB| + +## References + +https://huggingface.co/Somah/Model3_Marabertv2_T2_WS_A100 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-model4_arabertv2_base_t1_ws_a100_en.md b/docs/_posts/ahmedlone127/2023-10-26-model4_arabertv2_base_t1_ws_a100_en.md new file mode 100644 index 00000000000000..171fb5f7cf6719 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-model4_arabertv2_base_t1_ws_a100_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English model4_arabertv2_base_t1_ws_a100 BertForSequenceClassification from Somah +author: John Snow Labs +name: model4_arabertv2_base_t1_ws_a100 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model4_arabertv2_base_t1_ws_a100` is a English model originally trained by Somah. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model4_arabertv2_base_t1_ws_a100_en_5.1.4_3.4_1698282957194.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model4_arabertv2_base_t1_ws_a100_en_5.1.4_3.4_1698282957194.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("model4_arabertv2_base_t1_ws_a100","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("model4_arabertv2_base_t1_ws_a100","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model4_arabertv2_base_t1_ws_a100| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|507.3 MB| + +## References + +https://huggingface.co/Somah/Model4_arabertv2_base_T1_WS_A100 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-model4_arabertv2_base_t2_ws_a100_en.md b/docs/_posts/ahmedlone127/2023-10-26-model4_arabertv2_base_t2_ws_a100_en.md new file mode 100644 index 00000000000000..8cd7f7a68df1a7 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-model4_arabertv2_base_t2_ws_a100_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English model4_arabertv2_base_t2_ws_a100 BertForSequenceClassification from Somah +author: John Snow Labs +name: model4_arabertv2_base_t2_ws_a100 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model4_arabertv2_base_t2_ws_a100` is a English model originally trained by Somah. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model4_arabertv2_base_t2_ws_a100_en_5.1.4_3.4_1698285029764.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model4_arabertv2_base_t2_ws_a100_en_5.1.4_3.4_1698285029764.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("model4_arabertv2_base_t2_ws_a100","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("model4_arabertv2_base_t2_ws_a100","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model4_arabertv2_base_t2_ws_a100| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|507.3 MB| + +## References + +https://huggingface.co/Somah/Model4_arabertv2_base_T2_WS_A100 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-model5_arabertv2_large_t1_wos_en.md b/docs/_posts/ahmedlone127/2023-10-26-model5_arabertv2_large_t1_wos_en.md new file mode 100644 index 00000000000000..1b0a79f3369167 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-model5_arabertv2_large_t1_wos_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English model5_arabertv2_large_t1_wos BertForSequenceClassification from Somah +author: John Snow Labs +name: model5_arabertv2_large_t1_wos +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`model5_arabertv2_large_t1_wos` is a English model originally trained by Somah. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/model5_arabertv2_large_t1_wos_en_5.1.4_3.4_1698280773812.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/model5_arabertv2_large_t1_wos_en_5.1.4_3.4_1698280773812.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("model5_arabertv2_large_t1_wos","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("model5_arabertv2_large_t1_wos","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|model5_arabertv2_large_t1_wos| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.4 GB| + +## References + +https://huggingface.co/Somah/Model5_arabertv2_large_T1_WOS \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-scibert_uncased_finetuned_coda19_en.md b/docs/_posts/ahmedlone127/2023-10-26-scibert_uncased_finetuned_coda19_en.md new file mode 100644 index 00000000000000..cedddcc9d94321 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-scibert_uncased_finetuned_coda19_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English scibert_uncased_finetuned_coda19 BertForSequenceClassification from appleternity +author: John Snow Labs +name: scibert_uncased_finetuned_coda19 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`scibert_uncased_finetuned_coda19` is a English model originally trained by appleternity. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/scibert_uncased_finetuned_coda19_en_5.1.4_3.4_1698292747572.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/scibert_uncased_finetuned_coda19_en_5.1.4_3.4_1698292747572.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("scibert_uncased_finetuned_coda19","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("scibert_uncased_finetuned_coda19","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|scibert_uncased_finetuned_coda19| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|412.2 MB| + +## References + +https://huggingface.co/appleternity/scibert-uncased-finetuned-coda19 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-thext_ai_scibert_en.md b/docs/_posts/ahmedlone127/2023-10-26-thext_ai_scibert_en.md new file mode 100644 index 00000000000000..9bff0b0c5bd90f --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-thext_ai_scibert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English thext_ai_scibert BertForSequenceClassification from morenolq +author: John Snow Labs +name: thext_ai_scibert +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`thext_ai_scibert` is a English model originally trained by morenolq. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/thext_ai_scibert_en_5.1.4_3.4_1698280667934.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/thext_ai_scibert_en_5.1.4_3.4_1698280667934.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("thext_ai_scibert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("thext_ai_scibert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|thext_ai_scibert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|412.1 MB| + +## References + +https://huggingface.co/morenolq/thext-ai-scibert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-thext_bio_scibert_en.md b/docs/_posts/ahmedlone127/2023-10-26-thext_bio_scibert_en.md new file mode 100644 index 00000000000000..0739ffc6a2f76d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-thext_bio_scibert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English thext_bio_scibert BertForSequenceClassification from morenolq +author: John Snow Labs +name: thext_bio_scibert +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`thext_bio_scibert` is a English model originally trained by morenolq. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/thext_bio_scibert_en_5.1.4_3.4_1698281670639.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/thext_bio_scibert_en_5.1.4_3.4_1698281670639.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("thext_bio_scibert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("thext_bio_scibert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|thext_bio_scibert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|412.1 MB| + +## References + +https://huggingface.co/morenolq/thext-bio-scibert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-thext_czech_scibert_en.md b/docs/_posts/ahmedlone127/2023-10-26-thext_czech_scibert_en.md new file mode 100644 index 00000000000000..3b07c997774d9e --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-thext_czech_scibert_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English thext_czech_scibert BertForSequenceClassification from morenolq +author: John Snow Labs +name: thext_czech_scibert +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`thext_czech_scibert` is a English model originally trained by morenolq. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/thext_czech_scibert_en_5.1.4_3.4_1698282612468.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/thext_czech_scibert_en_5.1.4_3.4_1698282612468.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("thext_czech_scibert","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("thext_czech_scibert","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|thext_czech_scibert| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|412.1 MB| + +## References + +https://huggingface.co/morenolq/thext-cs-scibert \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-tiny_bert_cola_128_distilled_en.md b/docs/_posts/ahmedlone127/2023-10-26-tiny_bert_cola_128_distilled_en.md new file mode 100644 index 00000000000000..e90a97e47bd212 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-tiny_bert_cola_128_distilled_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tiny_bert_cola_128_distilled BertForSequenceClassification from Sayan01 +author: John Snow Labs +name: tiny_bert_cola_128_distilled +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_cola_128_distilled` is a English model originally trained by Sayan01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_cola_128_distilled_en_5.1.4_3.4_1698289915459.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_cola_128_distilled_en_5.1.4_3.4_1698289915459.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_cola_128_distilled","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_cola_128_distilled","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_cola_128_distilled| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/Sayan01/tiny-bert-cola-128-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-tiny_bert_qnli128_distilled_en.md b/docs/_posts/ahmedlone127/2023-10-26-tiny_bert_qnli128_distilled_en.md new file mode 100644 index 00000000000000..6cbdae4e630130 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-tiny_bert_qnli128_distilled_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tiny_bert_qnli128_distilled BertForSequenceClassification from Sayan01 +author: John Snow Labs +name: tiny_bert_qnli128_distilled +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_qnli128_distilled` is a English model originally trained by Sayan01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_qnli128_distilled_en_5.1.4_3.4_1698290311397.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_qnli128_distilled_en_5.1.4_3.4_1698290311397.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_qnli128_distilled","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_qnli128_distilled","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_qnli128_distilled| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/Sayan01/tiny-bert-qnli128-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-tiny_bert_qnli_128_distilled_en.md b/docs/_posts/ahmedlone127/2023-10-26-tiny_bert_qnli_128_distilled_en.md new file mode 100644 index 00000000000000..c5ab84cec9e0d3 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-tiny_bert_qnli_128_distilled_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tiny_bert_qnli_128_distilled BertForSequenceClassification from Sayan01 +author: John Snow Labs +name: tiny_bert_qnli_128_distilled +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_qnli_128_distilled` is a English model originally trained by Sayan01. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_qnli_128_distilled_en_5.1.4_3.4_1698289506883.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_qnli_128_distilled_en_5.1.4_3.4_1698289506883.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_qnli_128_distilled","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_qnli_128_distilled","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_qnli_128_distilled| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/Sayan01/tiny-bert-qnli-128-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-tiny_bert_sst2_distilled_linxi_en.md b/docs/_posts/ahmedlone127/2023-10-26-tiny_bert_sst2_distilled_linxi_en.md new file mode 100644 index 00000000000000..387c6c377b3f79 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-tiny_bert_sst2_distilled_linxi_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tiny_bert_sst2_distilled_linxi BertForSequenceClassification from linxi +author: John Snow Labs +name: tiny_bert_sst2_distilled_linxi +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tiny_bert_sst2_distilled_linxi` is a English model originally trained by linxi. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tiny_bert_sst2_distilled_linxi_en_5.1.4_3.4_1698279766472.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tiny_bert_sst2_distilled_linxi_en_5.1.4_3.4_1698279766472.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_sst2_distilled_linxi","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tiny_bert_sst2_distilled_linxi","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tiny_bert_sst2_distilled_linxi| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|16.7 MB| + +## References + +https://huggingface.co/linxi/tiny-bert-sst2-distilled \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-tinybertje_v2_en.md b/docs/_posts/ahmedlone127/2023-10-26-tinybertje_v2_en.md new file mode 100644 index 00000000000000..97b5099122006c --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-tinybertje_v2_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English tinybertje_v2 BertForSequenceClassification from GeniusVoice +author: John Snow Labs +name: tinybertje_v2 +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`tinybertje_v2` is a English model originally trained by GeniusVoice. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/tinybertje_v2_en_5.1.4_3.4_1698291480102.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/tinybertje_v2_en_5.1.4_3.4_1698291480102.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("tinybertje_v2","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("tinybertje_v2","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|tinybertje_v2| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|32.5 MB| + +## References + +https://huggingface.co/GeniusVoice/tinybertje-v2 \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-validate_bert_base_en.md b/docs/_posts/ahmedlone127/2023-10-26-validate_bert_base_en.md new file mode 100644 index 00000000000000..2f09064b031c55 --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-validate_bert_base_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English validate_bert_base BertForSequenceClassification from yashveer11 +author: John Snow Labs +name: validate_bert_base +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`validate_bert_base` is a English model originally trained by yashveer11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/validate_bert_base_en_5.1.4_3.4_1698283057312.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/validate_bert_base_en_5.1.4_3.4_1698283057312.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("validate_bert_base","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("validate_bert_base","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|validate_bert_base| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|409.4 MB| + +## References + +https://huggingface.co/yashveer11/validate_bert_base \ No newline at end of file diff --git a/docs/_posts/ahmedlone127/2023-10-26-validate_bert_large_en.md b/docs/_posts/ahmedlone127/2023-10-26-validate_bert_large_en.md new file mode 100644 index 00000000000000..789921ec14ea3d --- /dev/null +++ b/docs/_posts/ahmedlone127/2023-10-26-validate_bert_large_en.md @@ -0,0 +1,97 @@ +--- +layout: model +title: English validate_bert_large BertForSequenceClassification from yashveer11 +author: John Snow Labs +name: validate_bert_large +date: 2023-10-26 +tags: [bert, en, open_source, sequence_classification, onnx] +task: Text Classification +language: en +edition: Spark NLP 5.1.4 +spark_version: 3.4 +supported: true +engine: onnx +annotator: BertForSequenceClassification +article_header: + type: cover +use_language_switcher: "Python-Scala-Java" +--- + +## Description + +Pretrained BertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`validate_bert_large` is a English model originally trained by yashveer11. + +{:.btn-box} + + +[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/validate_bert_large_en_5.1.4_3.4_1698285228683.zip){:.button.button-orange.button-orange-trans.arr.button-icon} +[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/validate_bert_large_en_5.1.4_3.4_1698285228683.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3} + +## How to use + + + +
+{% include programmingLanguageSelectScalaPythonNLU.html %} +```python + +document_assembler = DocumentAssembler()\ + .setInputCol("text")\ + .setOutputCol("document") + +tokenizer = Tokenizer()\ + .setInputCols("document")\ + .setOutputCol("token") + +sequenceClassifier = BertForSequenceClassification.pretrained("validate_bert_large","en")\ + .setInputCols(["document","token"])\ + .setOutputCol("class") + +pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier]) + +data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text") + +result = pipeline.fit(data).transform(data) + +``` +```scala + +val document_assembler = new DocumentAssembler() + .setInputCol("text") + .setOutputCol("document") + +val tokenizer = new Tokenizer() + .setInputCols("document") + .setOutputCol("token") + +val sequenceClassifier = BertForSequenceClassification.pretrained("validate_bert_large","en") + .setInputCols(Array("document","token")) + .setOutputCol("class") + +val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, sequenceClassifier)) + +val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text") + +val result = pipeline.fit(data).transform(data) + + +``` +
+ +{:.model-param} +## Model Information + +{:.table-model} +|---|---| +|Model Name:|validate_bert_large| +|Compatibility:|Spark NLP 5.1.4+| +|License:|Open Source| +|Edition:|Official| +|Input Labels:|[documents, token]| +|Output Labels:|[class]| +|Language:|en| +|Size:|1.3 GB| + +## References + +https://huggingface.co/yashveer11/validate_bert_large \ No newline at end of file