2023-10-24-bert_cn_finetuning_18811449050_en

docs/_posts/ahmedlone127/2023-10-24-bert_base_arabertv2_finetuned_emotion_aetd2_en.md

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+---
+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

docs/_posts/ahmedlone127/2023-10-24-bert_base_arabic_camelbert_msa_sixteenth_xnli_finetuned_vish88_en.md

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+---
+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

docs/_posts/ahmedlone127/2023-10-24-bert_base_arabic_camelbert_msa_xnli_finetuned_en.md

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+---
+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

docs/_posts/ahmedlone127/2023-10-24-bert_base_cased_finetuned_mnli_en.md

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+---
+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