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 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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 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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 <ahmedlone127@gmail.com>
JohnSnowLabs · Oct 25, 2023 · b505d77 · b505d77
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diff --git a/...posts/ahmedlone127/2023-10-24-bert_base_arabertv2_finetuned_emotion_aetd2_en.md b/...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}
+<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_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
+
+
+
+<div class="tabs-box" markdown="1">
+{% 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)
+
+
+```
+</div>
+
+{:.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
diff --git a/...2023-10-24-bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_vish88_en.md b/...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}
+<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_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
+
+
+
+<div class="tabs-box" markdown="1">
+{% 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)
+
+
+```
+</div>
+
+{:.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
diff --git a/...sts/ahmedlone127/2023-10-24-bert_base_arabic_camelbert_msa_xnli_finetuned_en.md b/...sts/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}
+<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_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
+
+
+
+<div class="tabs-box" markdown="1">
+{% 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)
+
+
+```
+</div>
+
+{:.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
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
@@ -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}
+<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_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
+
+
+
+<div class="tabs-box" markdown="1">
+{% 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)
+
+
+```
+</div>
+
+{:.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