2023-11-14-bert_qa_base_parsbert_uncased_finetuned_squad_fa (#14068)

* Add model 2023-11-14-bert_qa_case_base_en * Add model 2023-11-14-bert_qa_bert_multi_cased_finetuned_chaii_en * Add model 2023-11-14-bert_qa_fine_tuned_tweetqa_aip_en * Add model 2023-11-14-bert_qa_bert_uncased_l_10_h_512_a_8_cord19_200616_squad2_en * Add model 2023-11-14-bert_qa_bert_multi_cased_finedtuned_xquad_tydiqa_goldp_xx * Add model 2023-11-14-bert_qa_bert_uncased_l_4_h_512_a_8_cord19_200616_squad2_en * Add model 2023-11-14-bert_qa_hkhkhkhk_finetuned_squad_en * Add model 2023-11-14-bert_qa_bert_large_uncased_whole_word_masking_finetuned_squadv2_en * Add model 2023-11-14-bert_qa_cgt_roberta_wwm_ext_large_zh * Add model 2023-11-14-bert_qa_bert_multi_cased_finetuned_xquadv1_finetuned_squad_colab_en * Add model 2023-11-14-bert_qa_hungarian_fine_tuned_hungarian_squadv2_hu * Add model 2023-11-14-bert_qa_chemical_bert_uncased_squad2_en * Add model 2023-11-14-bert_qa_bert_qasper_en * Add model 2023-11-14-bert_qa_huawei_noahtiny_general_6l_768_hotpot_en * Add model 2023-11-14-bert_qa_bertserini_bert_large_squad_en * Add model 2023-11-14-bert_qa_bert_mini_5_finetuned_squadv2_en * Add model 2023-11-14-bert_qa_bert_medium_squad2_distilled_en * Add model 2023-11-14-bert_qa_bert_medium_finetuned_squad_en * Add model 2023-11-14-bert_qa_bert_set_date_1_lr_2e_5_bosnian_32_ep_4_en * Add model 2023-11-14-bert_qa_bert_small_finetuned_squadv2_en * Add model 2023-11-14-bert_qa_komrc_train_ko * Add model 2023-11-14-bert_qa_chinese_pert_large_open_domain_mrc_zh * Add model 2023-11-14-bert_qa_bert_tiny_finetuned_squadv2_en * Add model 2023-11-14-bert_qa_bert_multi_cased_finedtuned_xquad_chaii_en * Add model 2023-11-14-bert_qa_biobert_squad2_cased_en * Add model 2023-11-14-bert_qa_bert_uncased_l_10_h_512_a_8_cord19_200616_squad2_covid_qna_en * Add model 2023-11-14-bert_qa_large_uncased_finetuned_infovqa_en * Add model 2023-11-14-bert_qa_biobert_bioasq_en * Add model 2023-11-14-bert_qa_bert_multi_uncased_finetuned_chaii_en * Add model 2023-11-14-bert_qa_chinese_pretrain_mrc_roberta_wwm_ext_large_zh * Add model 2023-11-14-bert_qa_bert_uncased_l_2_h_512_a_8_cord19_200616_squad2_en * Add model 2023-11-14-bert_qa_bert_uncased_l_10_h_512_a_8_squad2_en * Add model 2023-11-14-bert_qa_biobert_v1.1_pubmed_squad_v2_en * Add model 2023-11-14-bert_qa_bert_uncased_l_4_h_512_a_8_cord19_200616_squad2_covid_qna_en * Add model 2023-11-14-bert_qa_chinesebert_zh * Add model 2023-11-14-bert_qa_bert_tiny_2_finetuned_squadv2_en * Add model 2023-11-14-bert_qa_bert_uncased_l_4_h_768_a_12_squad2_en * Add model 2023-11-14-bert_qa_bsnmldb_finetuned_squad_en * Add model 2023-11-14-bert_qa_bert_tiny_5_finetuned_squadv2_en * Add model 2023-11-14-bert_qa_biobert_v1.1_biomedicalquestionanswering_en * Add model 2023-11-14-bert_qa_bert_uncased_l_4_h_768_a_12_squad2_covid_qna_en * Add model 2023-11-14-bert_qa_large_uncased_finetuned_vietnamese_infovqa_en * Add model 2023-11-14-bert_qa_chinese_question_answering_zh * Add model 2023-11-14-bert_qa_bert_turkish_question_answering_tr * Add model 2023-11-14-bert_qa_bert_uncased_l_4_h_256_a_4_squad2_covid_qna_en * Add model 2023-11-14-bert_qa_lewtun_finetuned_squad_en * Add model 2023-11-14-bert_qa_large_uncased_finetuned_squadv1_en * Add model 2023-11-14-bert_qa_bert_uncased_l_4_h_512_a_8_squad2_en * Add model 2023-11-14-bert_qa_cuad_pol_good_en * Add model 2023-11-14-bert_qa_bertlargeabsa_en * Add model 2023-11-14-bert_qa_deepset_bert_base_uncased_squad2_en * Add model 2023-11-14-bert_qa_bert_uncased_l_4_h_768_a_12_cord19_200616_squad2_covid_qna_en * Add model 2023-11-14-bert_qa_bert_uncased_l_6_h_128_a_2_squad2_en * Add model 2023-11-14-bert_qa_deepset_minilm_uncased_squad2_orkg_how_5e_05_en * Add model 2023-11-14-bert_qa_bertserini_base_cmrc_en * Add model 2023-11-14-bert_qa_cuad_pol_bad_en * Add model 2023-11-14-bert_qa_bertfast_02_en * Add model 2023-11-14-bert_qa_danish_bert_botxo_qa_squad_da * Add model 2023-11-14-bert_qa_linkbert_large_finetuned_squad_en * Add model 2023-11-14-bert_qa_biobert_base_cased_v1.1_squad_en * Add model 2023-11-14-bert_qa_bertserini_bert_base_squad_en * Add model 2023-11-14-bert_qa_m_xx * Add model 2023-11-14-bert_qa_darshana1406_base_multilingual_cased_finetuned_squad_xx * Add model 2023-11-14-bert_qa_demo_en * Add model 2023-11-14-bert_qa_biobert_base_cased_v1.1_squad_finetuned_biobert_en * Add model 2023-11-14-bert_qa_mbert_all_tahitian_sqen_sq20_1_en * Add model 2023-11-14-bert_qa_beto_base_spanish_squades2_es * Add model 2023-11-14-bert_qa_dbg_finetuned_squad_en * Add model 2023-11-14-bert_qa_biobert_v1.1_pubmed_finetuned_squad_en * Add model 2023-11-14-bert_qa_biobert_base_cased_v1.1_squad_finetuned_covdrobert_en * Add model 2023-11-14-bert_qa_macsquad_en * Add model 2023-11-14-bert_qa_distilbert_base_uncased_finetuned_custom_en * Add model 2023-11-14-bert_qa_bioformer_cased_v1.0_squad1_en * Add model 2023-11-14-bert_qa_deep_pavlov_full_ru * Add model 2023-11-14-bert_qa_mbert_finetuned_mlqa_english_hindi_dev_xx * Add model 2023-11-14-bert_qa_financial_v2_en * Add model 2023-11-14-bert_qa_deepset_minilm_uncased_squad2_orkg_how_1e_4_en * Add model 2023-11-14-bert_qa_mbert_finetuned_mlqa_vietnamese_hindi_dev_xx * Add model 2023-11-14-bert_qa_biobert_large_cased_v1.1_squad_en * Add model 2023-11-14-bert_qa_deepset_minilm_uncased_squad2_orkg_norwegian_label_5e_05_en * Add model 2023-11-14-bert_qa_deepset_minilm_uncased_squad2_orkg_what_1e_4_en * Add model 2023-11-14-bert_qa_mkkc58_finetuned_squad_en * Add model 2023-11-14-bert_qa_braquad_bert_qna_en * Add model 2023-11-14-bert_qa_biomedical_slot_filling_reader_large_en * Add model 2023-11-14-bert_qa_finetune_bert_base_v1_en * Add model 2023-11-14-bert_qa_finetune_scibert_v2_en * Add model 2023-11-14-bert_qa_faquad_base_portuguese_cased_pt * Add model 2023-11-14-bert_qa_modelontquad_tr * Add model 2023-11-14-bert_qa_finetuned_custom_2_en * Add model 2023-11-14-bert_qa_chinese_pert_large_mrc_zh * Add model 2023-11-14-bert_qa_monakth_base_cased_finetuned_squad_en * Add model 2023-11-14-bert_qa_causal_qa_en * Add model 2023-11-14-bert_qa_fewrel_zero_shot_en * Add model 2023-11-14-bert_qa_fpdm_hier_bert_ft_newsqa_en * Add model 2023-11-14-bert_qa_cyrusmv_finetuned_squad_en * Add model 2023-11-14-bert_qa_mqa_baseline_en * Add model 2023-11-14-bert_qa_deepset_minilm_uncased_squad2_orkg_what_5e_05_en * Add model 2023-11-14-bert_qa_fine_tuned_squad_aip_en * Add model 2023-11-14-bert_qa_hebert_finetuned_hebrew_squad_he * Add model 2023-11-14-bert_qa_deepset_minilm_uncased_squad2_orkg_which_5e_05_en * Add model 2023-11-14-bert_qa_chinese_pretrain_mrc_macbert_large_zh * Add model 2023-11-14-bert_qa_multilingual_bert_base_cased_english_en * Add model 2023-11-14-bert_qa_covidbert_squad_en * Add model 2023-11-14-bert_qa_finetuned_uia_en * Add model 2023-11-14-bert_qa_ixambert_finetuned_squad_en * Add model 2023-11-14-bert_qa_dl4nlp_group11_xtremedistil_l6_h256_uncased_squad_en * Add model 2023-11-14-bert_qa_distill_bert_base_spanish_wwm_cased_finetuned_spa_squad2_spanish_mrm8488_es * Add model 2023-11-14-bert_qa_firmanindolanguagemodel_id * Add model 2023-11-14-bert_qa_jatinshah_bert_finetuned_squad_en * Add model 2023-11-14-bert_qa_dylan1999_finetuned_squad_en * Add model 2023-11-14-bert_qa_fpdm_bert_ft_nepal_bhasa_newsqa_en * Add model 2023-11-14-bert_qa_deberta_v3_base_en * Add model 2023-11-14-bert_qa_muril_large_cased_hita_qa_hi * Add model 2023-11-14-bert_qa_kd_squad1.1_en * Add model 2023-11-14-bert_qa_fpdm_triplet_bert_ft_newsqa_en * Add model 2023-11-14-bert_qa_csarron_bert_base_uncased_squad_v1_en * Add model 2023-11-14-bert_qa_finetuned_custom_en * Add model 2023-11-14-bert_qa_nausheen_finetuned_squad_accelera_en * Add model 2023-11-14-bert_qa_debug_squad_en * Add model 2023-11-14-bert_qa_hendrixcosta_en * Add model 2023-11-14-bert_qa_kflash_finetuned_squad_en * Add model 2023-11-14-bert_qa_neuralmind_base_portuguese_squad_pt * Add model 2023-11-14-bert_qa_deep_pavlov_full_2_ru * Add model 2023-11-14-bert_qa_huggingface_course_bert_finetuned_squad_en * Add model 2023-11-14-bert_qa_korean_finetuned_klue_v2_ko * Add model 2023-11-14-bert_qa_kflash_finetuned_squad_accelera_en * Add model 2023-11-14-bert_qa_fpdm_hier_bert_ft_nepal_bhasa_newsqa_en * Add model 2023-11-14-bert_qa_deepset_minilm_uncased_squad2_orkg_which_1e_4_en * Add model 2023-11-14-bert_qa_huggingface_course_bert_finetuned_squad_accelerate_en * Add model 2023-11-14-bert_qa_ofirzaf_bert_large_uncased_squad_en * Add model 2023-11-14-bert_qa_hf_internal_testing_tiny_random_forquestionanswering_ja * Add model 2023-11-14-bert_qa_deepset_minilm_uncased_squad2_orkg_norwegian_label_1e_4_en * Add model 2023-11-14-bert_qa_finetuned_squad_transformerfrozen_testtoken_en * Add model 2023-11-14-bert_qa_fpdm_triplet_bert_ft_nepal_bhasa_newsqa_en * Add model 2023-11-14-bert_qa_dry_finetuned_squad_en * Add model 2023-11-15-bert_qa_indo_finetune_tydi_transfer_indo_in * Add model 2023-11-15-bert_qa_dylan1999_finetuned_squad_accelerate_en * Add model 2023-11-14-bert_qa_kobert_finetuned_klue_v2_ko * Add model 2023-11-15-bert_qa_large_japanese_wikipedia_ud_head_ja * Add model 2023-11-15-bert_qa_howey_bert_large_uncased_squad_en * Add model 2023-11-15-bert_qa_mbert_finetuned_mlqa_arabic_hindi_dev_xx * Add model 2023-11-15-bert_qa_pert_zh * Add model 2023-11-15-bert_qa_peterhsu_bert_finetuned_squad_en * Add model 2023-11-15-bert_qa_fabianwillner_base_uncased_finetuned_squad_en * Add model 2023-11-15-bert_qa_mbert_finetuned_mlqa_chinese_hindi_dev_xx * Add model 2023-11-15-bert_qa_mini_finetuned_squad_en * Add model 2023-11-15-bert_qa_internetoftim_bert_large_uncased_squad_en * Add model 2023-11-15-bert_qa_peterhsu_bert_finetuned_squad_accelerate_en * Add model 2023-11-15-bert_qa_indo_base_uncased_finetuned_tydi_indo_in * Add model 2023-11-15-bert_qa_hubert_fine_tuned_hungarian_squadv1_hu * Add model 2023-11-15-bert_qa_monakth_base_uncased_finetuned_squad_en * Add model 2023-11-15-bert_qa_finetune_bert_base_v3_en * Add model 2023-11-15-bert_qa_jimypbr_bert_base_uncased_squad_en * Add model 2023-11-15-bert_qa_finetune_bert_base_v2_en * Add model 2023-11-15-bert_qa_pubmed_bert_squadv2_en * Add model 2023-11-15-bert_qa_mrp_bert_finetuned_squad_en * Add model 2023-11-15-bert_qa_finetuned_custom_1_en * Add model 2023-11-15-bert_qa_kamilali_distilbert_base_uncased_finetuned_squad_en * Add model 2023-11-15-bert_qa_qgrantq_finetuned_squad_en * Add model 2023-11-15-bert_qa_large_squad_en * Add model 2023-11-15-bert_qa_multilingual_bert_base_cased_spanish_es * Add model 2023-11-15-bert_qa_fpdm_bert_ft_newsqa_en * Add model 2023-11-15-bert_qa_kaporter_bert_base_uncased_finetuned_squad_en * Add model 2023-11-15-bert_qa_question_answering_cased_squadv2_tr * Add model 2023-11-15-bert_qa_linkbert_base_finetuned_squad_en * Add model 2023-11-15-bert_qa_fpdm_pert_sent_0.01_squad2.0_en * Add model 2023-11-15-bert_qa_kcbert_base_finetuned_squad_ko * Add model 2023-11-15-bert_qa_question_answering_uncased_squadv2_tr * Add model 2023-11-15-bert_qa_indo_base_indonesian_finetune_idk_mrc_id * Add model 2023-11-15-bert_qa_keepitreal_finetuned_squad_en * Add model 2023-11-15-bert_qa_burmese_model_en * Add model 2023-11-15-bert_qa_loodos_bert_base_uncased_qa_fine_tuned_tr * Add model 2023-11-15-bert_qa_quote_attribution_en * Add model 2023-11-15-bert_qa_multilingual_bert_base_cased_vietnamese_vi * Add model 2023-11-15-bert_qa_khanh_base_multilingual_cased_finetuned_squad_en * Add model 2023-11-15-bert_qa_indo_finetuned_squad_id * Add model 2023-11-15-bert_qa_ner_conll_base_uncased_en * Add model 2023-11-15-bert_qa_irenelizihui_finetuned_squad_en * Add model 2023-11-15-bert_qa_neuralmagic_bert_squad_12layer_0sparse_en * Add model 2023-11-15-bert_qa_klue_bert_base_aihub_mrc_ko * Add model 2023-11-15-bert_qa_mbert_finetuned_mlqa_dev_en * Add model 2023-11-15-bert_qa_ixambert_finetuned_squad_basque_marcbrun_eu * Add model 2023-11-15-bert_qa_mbert_finetuned_mlqa_english_chinese_hindi_dev_xx * Add model 2023-11-15-bert_qa_salti_bert_base_multilingual_cased_finetuned_squad_xx * Add model 2023-11-15-bert_qa_kobert_finetuned_squad_kor_v1_ko * Add model 2023-11-15-bert_qa_korean_lm_finetuned_klue_v2_ko * Add model 2023-11-15-bert_qa_mbert_finetuned_mlqa_spanish_hindi_dev_xx * Add model 2023-11-15-bert_qa_nolog_scibert_v2_en * Add model 2023-11-15-bert_qa_minilm_uncased_squad2_en * Add model 2023-11-15-bert_qa_pars_question_answering_pquad_fa * Add model 2023-11-15-bert_qa_modelbin_en * Add model 2023-11-15-bert_qa_large_en * Add model 2023-11-15-bert_qa_sber_full_tes_ru * Add model 2023-11-15-bert_qa_multilingual_base_cased_chines_zh * Add model 2023-11-15-bert_qa_mqa_cls_en * Add model 2023-11-15-bert_qa_sbert_large_nlu_russian_finetuned_squad_en * Add model 2023-11-15-bert_qa_ruselkomp_sbert_large_nlu_russian_finetuned_squad_full_ru * Add model 2023-11-15-bert_qa_multi_uncased_trained_squadv2_en * Add model 2023-11-15-bert_qa_large_uncased_spanish_sign_language_en * Add model 2023-11-15-bert_qa_multilingual_bert_base_cased_german_de * Add model 2023-11-15-bert_qa_scibert_nli_squad_en * Add model 2023-11-15-bert_qa_logo_qna_model_tr * Add model 2023-11-15-bert_qa_multilingual_bert_base_cased_arabic_ar * Add model 2023-11-15-bert_qa_sangyongan30_finetuned_squad_en * Add model 2023-11-15-bert_qa_sd2_en * Add model 2023-11-15-bert_qa_sd2_small_en * Add model 2023-11-15-bert_qa_mymild_finetuned_squad_en * Add model 2023-11-15-bert_qa_muril_large_squad2_hi * Add model 2023-11-15-bert_qa_mbert_bengali_tydiqa_qa_bn * Add model 2023-11-15-bert_qa_set_date_1_lr_3e_5_bosnian_32_ep_3_en * Add model 2023-11-15-bert_qa_sci_squadv2_en * Add model 2023-11-15-bert_qa_mbert_finetuned_mlqa_german_hindi_dev_xx * Add model 2023-11-15-bert_qa_set_date_2_lr_2e_5_bosnian_32_ep_4_en * Add model 2023-11-15-bert_qa_mini_en * Add model 2023-11-15-bert_qa_norwegian_need_tonga_tonga_islands_name_this_en * Add model 2023-11-15-bert_qa_minilm_l12_h384_uncased_squad_en * Add model 2023-11-15-bert_qa_news_pretrain_bert_ft_newsqa_en * Add model 2023-11-15-bert_qa_neg_komrc_train_ko * Add model 2023-11-15-bert_qa_scibert_scivocab_uncased_squad_v2_en * Add model 2023-11-15-bert_qa_mod_7_squad_en * Add model 2023-11-15-bert_qa_shed_e_finetuned_squad_en * Add model 2023-11-15-bert_qa_news_pretrain_bert_ft_nepal_bhasa_newsqa_en * Add model 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_4_en * Add model 2023-11-15-bert_qa_pars_fa * Add model 2023-11-15-bert_qa_output_files_en * Add model 2023-11-15-bert_qa_paranoidandroid_finetuned_squad_en * Add model 2023-11-15-bert_qa_small_finetuned_cuad_longer_en * Add model 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_128_finetuned_squad_seed_0_en * Add model 2023-11-15-bert_qa_modelf_01_en * Add model 2023-11-15-bert_qa_parsbert_finetuned_persianqa_fa * Add model 2023-11-15-bert_qa_petros89_finetuned_squad_en * Add model 2023-11-15-bert_qa_scibert_scivocab_uncased_squad_en * Add model 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_0_en * Add model 2023-11-15-bert_qa_span_finetuned_squadv2_en * Add model 2023-11-15-bert_qa_qa_roberta_base_chinese_extractive_zh * Add model 2023-11-15-bert_qa_set_date_3_lr_2e_5_bosnian_32_ep_3_en * Add model 2023-11-15-bert_qa_pquad_fa * Add model 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_16_finetuned_squad_seed_2_en * Add model 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_10_en * Add model 2023-11-15-bert_qa_sirah_finetuned_squad_en * Add model 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_1024_finetuned_squad_seed_2_en * Add model 2023-11-15-bert_qa_model_output_en * Add model 2023-11-15-bert_qa_modelonwhol_tr * Add model 2023-11-15-bert_qa_modelv2_en * Add model 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_0_en * Add model 2023-11-15-bert_qa_qaconv_bert_large_uncased_whole_word_masking_squad2_en * Add model 2023-11-15-bert_qa_question_answering_chinese_zh * Add model 2023-11-15-bert_qa_monakth_base_multilingual_cased_finetuned_squad_xx * Add model 2023-11-15-bert_qa_spanbert_base_cased_few_shot_k_512_finetuned_squad_seed_4_en * Add model 2023-11-15-bert_qa_recipe_triplet_base_uncased_squadv2_epochs_3_en --------- Co-authored-by: ahmedlone127 <ahmedlone127@gmail.com>
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diff --git a/.../ahmedlone127/2023-11-14-bert_qa_base_multilingual_cased_finetuned_viquad_en.md b/.../ahmedlone127/2023-11-14-bert_qa_base_multilingual_cased_finetuned_viquad_en.md
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+---
+layout: model
+title: English BertForQuestionAnswering Base Cased model (from Khanh)
+author: John Snow Labs
+name: bert_qa_base_multilingual_cased_finetuned_viquad
+date: 2023-11-14
+tags: [en, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: en
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained Question Answering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-multilingual-cased-finetuned-viquad` is a English model originally trained by `Khanh`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_base_multilingual_cased_finetuned_viquad_en_5.2.0_3.0_1699993581067.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_base_multilingual_cased_finetuned_viquad_en_5.2.0_3.0_1699993581067.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+documentAssembler = MultiDocumentAssembler() \
+    .setInputCols(["question", "context"]) \
+    .setOutputCols(["document_question", "document_context"])
+
+spanClassifier = BertForQuestionAnswering.pretrained("bert_qa_base_multilingual_cased_finetuned_viquad","en") \
+    .setInputCols(["document_question", "document_context"]) \
+    .setOutputCol("answer")\
+    .setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[documentAssembler, spanClassifier])
+
+data = spark.createDataFrame([["What is my name?", "My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val documentAssembler = new MultiDocumentAssembler() 
+      .setInputCols(Array("question", "context")) 
+      .setOutputCols(Array("document_question", "document_context"))
+
+val spanClassifer = BertForQuestionAnswering.pretrained("bert_qa_base_multilingual_cased_finetuned_viquad","en") 
+    .setInputCols(Array("document", "token")) 
+    .setOutputCol("answer")
+    .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(documentAssembler, spanClassifier))
+
+val data = Seq("What is my name?", "My name is Clara and I live in Berkeley.").toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+
+{:.nlu-block}
+```python
+import nlu
+nlu.load("en.answer_question.bert.cased_multilingual_base_finetuned").predict("""What is my name?|||"My name is Clara and I live in Berkeley.""")
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_base_multilingual_cased_finetuned_viquad|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|en|
+|Size:|665.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/Khanh/bert-base-multilingual-cased-finetuned-viquad
diff --git a/.../_posts/ahmedlone127/2023-11-14-bert_qa_base_multilingual_cased_finetuned_xx.md b/.../_posts/ahmedlone127/2023-11-14-bert_qa_base_multilingual_cased_finetuned_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual BertForQuestionAnswering Base Cased model (from obokkkk)
+author: John Snow Labs
+name: bert_qa_base_multilingual_cased_finetuned
+date: 2023-11-14
+tags: [xx, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-multilingual-cased-finetuned` is a Multilingual model originally trained by `obokkkk`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_base_multilingual_cased_finetuned_xx_5.2.0_3.0_1699993678387.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_base_multilingual_cased_finetuned_xx_5.2.0_3.0_1699993678387.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_base_multilingual_cased_finetuned","xx")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_base_multilingual_cased_finetuned","xx")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_base_multilingual_cased_finetuned|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|xx|
+|Size:|665.0 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/obokkkk/bert-base-multilingual-cased-finetuned
diff --git a/...medlone127/2023-11-14-bert_qa_base_multilingual_uncased_finetuned_squadv2_xx.md b/...medlone127/2023-11-14-bert_qa_base_multilingual_uncased_finetuned_squadv2_xx.md
@@ -0,0 +1,94 @@
+---
+layout: model
+title: Multilingual BertForQuestionAnswering Base Uncased model (from khoanvm)
+author: John Snow Labs
+name: bert_qa_base_multilingual_uncased_finetuned_squadv2
+date: 2023-11-14
+tags: [xx, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: xx
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-multilingual-uncased-finetuned-squadv2` is a Multilingual model originally trained by `khoanvm`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_base_multilingual_uncased_finetuned_squadv2_xx_5.2.0_3.0_1699993920867.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_base_multilingual_uncased_finetuned_squadv2_xx_5.2.0_3.0_1699993920867.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_base_multilingual_uncased_finetuned_squadv2","xx")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_base_multilingual_uncased_finetuned_squadv2","xx")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_base_multilingual_uncased_finetuned_squadv2|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|xx|
+|Size:|625.5 MB|
+|Case sensitive:|false|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/khoanvm/bert-base-multilingual-uncased-finetuned-squadv2
diff --git a/docs/_posts/ahmedlone127/2023-11-14-bert_qa_base_nnish_cased_squad1_fi.md b/docs/_posts/ahmedlone127/2023-11-14-bert_qa_base_nnish_cased_squad1_fi.md
@@ -0,0 +1,96 @@
+---
+layout: model
+title: Finnish BertForQuestionAnswering Base Cased model (from ilmariky)
+author: John Snow Labs
+name: bert_qa_base_nnish_cased_squad1
+date: 2023-11-14
+tags: [fi, open_source, bert, question_answering, onnx]
+task: Question Answering
+language: fi
+edition: Spark NLP 5.2.0
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: BertForQuestionAnswering
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained BertForQuestionAnswering model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. `bert-base-finnish-cased-squad1-fi` is a Finnish model originally trained by `ilmariky`.
+
+## Predicted Entities
+
+
+
+{:.btn-box}
+<button class="button button-orange" disabled>Live Demo</button>
+<button class="button button-orange" disabled>Open in Colab</button>
+[Download](https://s3.amazonaws.com/auxdata.johnsnowlabs.com/public/models/bert_qa_base_nnish_cased_squad1_fi_5.2.0_3.0_1699993974738.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/bert_qa_base_nnish_cased_squad1_fi_5.2.0_3.0_1699993974738.zip){:.button.button-orange.button-orange-trans.button-icon.button-copy-s3}
+
+## How to use
+
+
+
+<div class="tabs-box" markdown="1">
+{% include programmingLanguageSelectScalaPythonNLU.html %}
+```python
+Document_Assembler = MultiDocumentAssembler()\
+     .setInputCols(["question", "context"])\
+     .setOutputCols(["document_question", "document_context"])
+
+Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_base_nnish_cased_squad1","fi")\
+     .setInputCols(["document_question", "document_context"])\
+     .setOutputCol("answer")\
+     .setCaseSensitive(True)
+
+pipeline = Pipeline(stages=[Document_Assembler, Question_Answering])
+
+data = spark.createDataFrame([["What's my name?","My name is Clara and I live in Berkeley."]]).toDF("question", "context")
+
+result = pipeline.fit(data).transform(data)
+```
+```scala
+val Document_Assembler = new MultiDocumentAssembler()
+     .setInputCols(Array("question", "context"))
+     .setOutputCols(Array("document_question", "document_context"))
+
+val Question_Answering = BertForQuestionAnswering.pretrained("bert_qa_base_nnish_cased_squad1","fi")
+     .setInputCols(Array("document_question", "document_context"))
+     .setOutputCol("answer")
+     .setCaseSensitive(true)
+
+val pipeline = new Pipeline().setStages(Array(Document_Assembler, Question_Answering))
+
+val data = Seq("What's my name?","My name is Clara and I live in Berkeley.").toDS.toDF("question", "context")
+
+val result = pipeline.fit(data).transform(data)
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|bert_qa_base_nnish_cased_squad1|
+|Compatibility:|Spark NLP 5.2.0+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[document_question, document_context]|
+|Output Labels:|[answer]|
+|Language:|fi|
+|Size:|464.7 MB|
+|Case sensitive:|true|
+|Max sentence length:|512|
+
+## References
+
+References
+
+- https://huggingface.co/ilmariky/bert-base-finnish-cased-squad1-fi
+- https://github.com/google-research-datasets/tydiqa
+- https://worksheets.codalab.org/rest/bundles/0x6b567e1cf2e041ec80d7098f031c5c9e/contents/blob/