2024-01-19-deberta_base_zero_shot_classifier_mnli_anli_v3_en

docs/_posts/ahmedlone127/2024-01-19-1_model_topic_classification_v2_en.md

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+---
+layout: model
+title: English 1_model_topic_classification_v2 CamemBertForSequenceClassification from boronbrown48
+author: John Snow Labs
+name: 1_model_topic_classification_v2
+date: 2024-01-19
+tags: [camembert, en, open_source, sequence_classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.2.4
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`1_model_topic_classification_v2` is a English model originally trained by boronbrown48.
+
+{:.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/1_model_topic_classification_v2_en_5.2.4_3.0_1705696757342.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/1_model_topic_classification_v2_en_5.2.4_3.0_1705696757342.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 = CamemBertForSequenceClassification.pretrained("1_model_topic_classification_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 = CamemBertForSequenceClassification.pretrained("1_model_topic_classification_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)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|1_model_topic_classification_v2|
+|Compatibility:|Spark NLP 5.2.4+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[documents, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|394.4 MB|
+
+## References
+
+https://huggingface.co/boronbrown48/1_model_topic_classification_v2

docs/_posts/ahmedlone127/2024-01-19-1_topic_classification_en.md

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+---
+layout: model
+title: English 1_topic_classification CamemBertForSequenceClassification from boronbrown48
+author: John Snow Labs
+name: 1_topic_classification
+date: 2024-01-19
+tags: [camembert, en, open_source, sequence_classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.2.4
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`1_topic_classification` is a English model originally trained by boronbrown48.
+
+{:.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/1_topic_classification_en_5.2.4_3.0_1705698324374.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/1_topic_classification_en_5.2.4_3.0_1705698324374.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 = CamemBertForSequenceClassification.pretrained("1_topic_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 = CamemBertForSequenceClassification.pretrained("1_topic_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)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|1_topic_classification|
+|Compatibility:|Spark NLP 5.2.4+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[documents, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|394.3 MB|
+
+## References
+
+https://huggingface.co/boronbrown48/1_topic_classification

docs/_posts/ahmedlone127/2024-01-19-492_model_depressed_en.md

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+---
+layout: model
+title: English 492_model_depressed CamemBertForSequenceClassification from tinsira
+author: John Snow Labs
+name: 492_model_depressed
+date: 2024-01-19
+tags: [camembert, en, open_source, sequence_classification, onnx]
+task: Text Classification
+language: en
+edition: Spark NLP 5.2.4
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`492_model_depressed` is a English model originally trained by tinsira.
+
+{:.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/492_model_depressed_en_5.2.4_3.0_1705701160714.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/492_model_depressed_en_5.2.4_3.0_1705701160714.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 = CamemBertForSequenceClassification.pretrained("492_model_depressed","en")\
+            .setInputCols(["document","token"])\
+            .setOutputCol("class")
+
+pipeline = Pipeline().setStages([document_assembler, tokenizer, sequenceClassifier])
+
+data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")
+
+result = pipeline.fit(data).transform(data)
+
+```
+```scala
+
+val document_assembler = new DocumentAssembler()
+    .setInputCol("text")
+    .setOutputCol("document")
+
+val tokenizer = new Tokenizer()
+    .setInputCols("document") 
+    .setOutputCol("token")  
+
+val sequenceClassifier = CamemBertForSequenceClassification.pretrained("492_model_depressed","en")
+            .setInputCols(Array("document","token"))
+            .setOutputCol("class")
+
+val pipeline = 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:|492_model_depressed|
+|Compatibility:|Spark NLP 5.2.4+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[documents, token]|
+|Output Labels:|[class]|
+|Language:|en|
+|Size:|394.3 MB|
+
+## References
+
+https://huggingface.co/tinsira/492-Model-Depressed

docs/_posts/ahmedlone127/2024-01-19-activity_classifier_fr.md

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+---
+layout: model
+title: French activity_classifier CamemBertForSequenceClassification from jeveuxaider
+author: John Snow Labs
+name: activity_classifier
+date: 2024-01-19
+tags: [camembert, fr, open_source, sequence_classification, onnx]
+task: Text Classification
+language: fr
+edition: Spark NLP 5.2.4
+spark_version: 3.0
+supported: true
+engine: onnx
+annotator: CamemBertForSequenceClassification
+article_header:
+  type: cover
+use_language_switcher: "Python-Scala-Java"
+---
+
+## Description
+
+Pretrained CamemBertForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP.`activity_classifier` is a French model originally trained by jeveuxaider.
+
+{:.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/activity_classifier_fr_5.2.4_3.0_1705696233271.zip){:.button.button-orange.button-orange-trans.arr.button-icon}
+[Copy S3 URI](s3://auxdata.johnsnowlabs.com/public/models/activity_classifier_fr_5.2.4_3.0_1705696233271.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 = CamemBertForSequenceClassification.pretrained("activity_classifier","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 = CamemBertForSequenceClassification.pretrained("activity_classifier","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)
+
+
+```
+</div>
+
+{:.model-param}
+## Model Information
+
+{:.table-model}
+|---|---|
+|Model Name:|activity_classifier|
+|Compatibility:|Spark NLP 5.2.4+|
+|License:|Open Source|
+|Edition:|Official|
+|Input Labels:|[documents, token]|
+|Output Labels:|[class]|
+|Language:|fr|
+|Size:|401.6 MB|
+
+## References
+
+https://huggingface.co/jeveuxaider/activity-classifier